School of Computer Science THE UNIVERSITY OF BIRMINGHAM Ghost Machine

Aaron Sloman

Created: 20 Dec 2009
Updated: 28 May 2015; 2 Sep 2015
30 Oct 2010; 23 Mar 2011; 14 Jun 2011; 24 Mar 2014; 11 Apr 2014; 28 Jul 2014
7 Jan 2010; 10 Jan 2010; 21 Jan 2010; 24 Jan 2010; 1 Mar 2010; 22 Mar 2010;


(Currently only 1962 - 1998)



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  1. Filename: Sloman.what.arch.pdf
    Title: What sort of architecture is required for a human-like agent?
    Author: Aaron Sloman
    In: M Wooldridge and A Rao (Eds), Foundations of Rational Agency,
    Kluwer Academic Publishers, 1999
    (Expanded version of: 1996 paper)
    Date: Installed 13 May 1997. Published 1999
    This paper is about how to give human-like powers to complete agents. For this the most important design choice concerns the overall architecture. Questions regarding detailed mechanisms, forms of representations, inference capabilities, knowledge etc. are best addressed in the context of a global architecture in which different design decisions need to be linked. Such a design would assemble various kinds of functionality into a complete coherent working system, in which there are many concurrent, partly independent, partly mutually supportive, partly potentially incompatible processes, addressing a multitude of issues on different time scales, including asynchronous, concurrent, motive generators. Designing human like agents is part of the more general problem of understanding design space, niche space and their interrelations, for, in the abstract, there is no one optimal design, as biological diversity on earth shows.
    [[This version includes diagrams not in the original version.]]

  2. Filename:
    Title: Review of Affective Computing by Rosalind Picard, MIT Press 1997.
    (in The AI Magazine April, 1999, with reply by Rosalind Picard.)
    Author: Aaron Sloman
    Date: Installed 9 Sept 1998. Published 1999


    This review summarises the main themes of Picard's book, some of which are related to Damasio's ideas in Descartes' Error. In particular, I try to show that not all secondary emotions need manifest themselves via the primary emotion system, and therefore they will not all be detectable by measurements of physiological changes. I agree with much of the spirit of the book, but disagree on detail.
    NOTE: Rosalind Picard's reply to this review is available online at

  3. Filename: Sloman.kd.pdf
    Title: Architectural Requirements for Human-like Agents Both Natural and Artificial. (What sorts of machines can love? )

    To appear in Human Cognition And Social Agent Technology Ed. Kerstin Dautenhahn, in the "Advances in Consciousness Research" series, John Benjamins Publishing
    (Extended version of slides on love for "Voice box" talk, below.)
    Authors: Aaron Sloman
    Date: 10 Jan 1999 (Book Published, March 2000)

    This paper, an expanded version of a talk on love given to a literary society, attempts to analyse some of the architectural requirements for an agent which is capable of having primary, secondary and tertiary emotions, including being infatuated or in love. It elaborates on work done previously in the Birmingham Cognition and Affect group, describing our proposed three level architecture (with reactive, deliberative and meta-management layers), showing how different sorts of emotions relate to those layers.

    Some of the relationships between emotional states involving partial loss of control of attention (e.g. emotional states involved in being in love) and other states which involve dispositions (e.g. attitudes such as loving) are discussed and related to the architecture.

    The work of poets and playwrights can be shown to involve an implicit commitment to the hypothesis that minds are (at least) information processing engines. Besides loving, many other familiar states and processes such as seeing, deciding, wondering whether, hoping, regretting, enjoying, disliking, learning, planning and acting all involve various sorts of information processing.

    By analysing the requirements for such processes to occur, and relating them to our evolutionary history and what is known about animal brains, and comparing this with what is being learnt from work on artificial minds in artificial intelligence, we can begin to formulate new and deeper theories about how minds work, including how we come to think about qualia, many forms of learning and development, and results of brain damage or abnormality.

    But there is much prejudice that gets in the way of such theorising, and also much misunderstanding because people construe notions of "information processing" too narrowly.

  4. Filename: Sloman.eace-interview.html
    Title: Patrice Terrier interviews Aaron Sloman for EACE QUARTERLY
    (August 1999)
    Date: 3 Sep 1999

    Patrice Terrier asks and Aaron Sloman attempts to answer questions about AI, about emotions, about the relevance of philosophy to AI, about Poplog, Sim_agent and other tools.
    (EACE = European Association for Cognitive Ergonomics

  5. Filename: (superseded version)
    Filename: Sloman.lmps99.pdf (superseded version)
    Title: Architecture-Based Conceptions Of Mind (Superseded version )

    (Abstract for invited talk at 11th International Congress of Logic, Methodology and Philosophy of Science, Krakow, Poland August 20-26, 1999.)

    NOTE: The link now points to the final, published version of the paper.

    Author: Aaron Sloman
    Date: 8 Jun 1999

    Abstract: (This was a short abstract. See later version)
    Because we apparently have direct access to the phenomena, it is tempting to think we know exactly what we are talking about when we refer to consciousness, experience, the "first-person" viewpoint, etc. But this is as mistaken as thinking we fully understand what simultaneity is just because we have direct access to the phenomena, for instance when we see a flash and hear a bang simultaneously.

    Einstein taught us otherwise. From the fact that we can recognise some instances of a concept it does not follow that we know what is meant in general by saying that something is or is not an instance. Endless debates about which animals and which types of machines have consciousness are among the many symptoms that our concepts of mentality are more confused than we realise.

    Too often people thinking about mind and consciousness consider only adult human minds in an academic culture, ignoring people from other cultures, infants, people with brain damage or disease, insects, birds, chimpanzees and other animals, as well as robots and software agents in synthetic environments. By broadening our view, we find evidence for diverse information processing architectures, each supporting and explaining a specific combination of mental capabilities.

    When concepts connote complex, clusters of capabilities, then different subsets may be present at different stages of development of a species or an individual. Very different subsets may be found in different species. Different subsets may be impaired by different sorts of brain damage or degeneration. When we know what sorts of components are implicitly referred to by our pre-theoretic "cluster concepts" we can then define new more precise concepts in terms of different subsets. It helps if we can specify the architectures which generate different subsets of information processing capabilities. That also enables us to ask new, deeper, questions not only about the development of individuals but about the evolution of mentality in different species.

    Architecture-based concepts generated in the framework of virtual machine functionalism subvert familiar philosophical thought experiments about zombies, since attempts to specify a zombie with the {\sc} right kind of {\em virtual machine} functionality but lacking our mental states degenerates into incoherence when spelled out in great detail. When you have fully described the internal states, processes, dispositions and causal interactions within a zombie whose information processing functions are alleged to be {\em exactly} like ours, the claim that something might still be missing becomes incomprehensible.

  6. Filename: (superseded version)
    Filename: Sloman.i3.pdf (superseded version)
    Title: Beyond Shallow Models of Emotion
    This paper has been superseded by a longer revised version with the same name in Cognitive Processing, Vol 1, 2001, pp 1-22, (Summer 2001), available in this directory via the 2000- Contents file.

    (Originally presented at I3 Spring Days Workshop on Behavior planning for life-like characters and avatars Sitges, Spain, March 1999)

    Author: Aaron Sloman
    Date: 3 Aug 1999

    There is much shallow thinking about emotions, and a huge diversity of definitions of "emotion" arises out of this shallowness. Too often the definitions and theories are inspired either by a mixture of introspection and selective common sense, or by a misdirected neo-behaviourist methodology, attempting to define emotions and other mental states in terms of observables. One way to avoid such shallowness, and perhaps achieve convergence, is to base concepts and theories on an information processing architecture, which is subject to various constraints, including evolvability, implementability, coping with resource-limited physical mechanisms, and achieving required functionality. Within such an architecture-based theory we can distinguish primary emotions, secondary emotions, and tertiary emotions, and produce a coherent theory which not only explains a wide range of phenomena but also partly explains the diversity of theories: most of them focus on only a subset of types of emotions.

  7. Filename:
    Filename: Sloman.bcs.hci.99.pdf
    Title: Why can't a goldfish long for its mother? Architectural prerequisites for various types of emotions.

    Slides (17 pages) for invited talk at Conference on
        Affective Computing: The Role of Emotion In HCI
    Saturday 10th April 1999, University College London. See the conference web site.)
    Author: Aaron Sloman
    Date: 11 Apr 1999
    (Intended as a partial antidote to wide-spread shallow views about emotions, and over-simplified ontologies too easily accepted by AI and HCI researchers now becoming interested in intelligence and affect.)

    Our everyday attributions of emotions, moods, attitudes, desires, and other affective states implicitly presuppose that people are information processors. To long for something you need to know of its existence, its remoteness, and the possibility of being together again. Besides these semantic information states, longing also involves a control state. One who has deep longing for X does not merely occasionally think it would be wonderful to be with X. In deep longing thoughts are often uncontrollably drawn to X.

    We need to understand the architectural underpinnings of control of attention, so that we can see how control can be lost. Having control requires being able to some extent to monitor one's thought processes, to evaluate them, and to redirect them. Only "to some extent" because both access and control are partial. We need to explain why. (In addition, self-evaluation can be misguided, e.g. after religious indoctrination!)

    "Tertiary emotions" like deep longing are different from "primary" emotions (e.g. being startled or sexually aroused) and "secondary emotions" (e.g. being apprehensive or relieved) which, to some extent, we share with other animals. Can chimps, bonobos or human toddlers have tertiary emotions? To clarify the empirical questions and explain the phenomena we need a good model of the information processing architecture.

    Conjecture: various modules in the human mind (perceptual, motor, and more central modules) all have architectural layers that evolved at different times and support different kinds of functionality, including reactive, deliberative and self-monitoring processes.

    Different types of affect are related to the functioning of these different layers: e.g. primary emotions require only reactive layers, secondary emotions require deliberative layers (including "what if" reasoning mechanisms) and tertiary emotions (e.g. deep longing, humiliation, infatuation) involve additional self evaluation and self control mechanisms which evolved late and may be rare among animals.

    An architecture-based framework can bring some order into the morass of studies of affect (e.g. myriad definitions of "emotion"). This will help us understand which kinds of emotions can arise in software agents that lack the reactive mechanisms required for controlling a physical body.

    HCI Designers need to understand these issues (a) if they want to model human affective processes, (b) if they wish to design systems which engage fruitfully with human affective processes, (c) if they wish to produce teaching/training packages for would-be counsellors, psychotherapists, psychologists.

  8. Filename: Sloman.Logan.cacm.pdf
    Filename: Sloman.Logan.cacm.pdf
    Title: Building cognitively rich agents using the SIM_AGENT toolkit,
    in Communications of the Association of Computing Machinery,
    March 1999, vol 43, no 2, pp. 71-77;
    Online (with inset report written by two users of the toolkit) at
    and also here.(PDF))
    Authors: Aaron Sloman and Brian Logan
    Date: 17 Jan 1999


    An overview of some of the motivation of our research and design criteria for the SIM_AGENT toolkit for a special issue of CACM on multi-agent systems, edited by Anupam Joshi and Munindar Singh.

    For more information about the toolkit (now referred to as SimAgent), including movies of demos, see

    Work on the Cognition and Affect project using the toolkit is reported here (PDF).


  9. Filename: Sloman_iberamia.pdf
    Title: The "Semantics" of Evolution: Trajectories and Trade-offs in Design Space and Niche Space.

    Author: Aaron Sloman
    Invited talk for 6th Iberoamerican Conference on AI (IBERAMIA-98) Lisbon, October 1998.
    In Progress in Artificial Intelligence, Springer, Lecture Notes in Artificial Intelligence, pp. 27--38, Editor Helder Coelho.
    Date: 16 Jun 1998


    This paper attempts to characterise a unifying overview of the practice of software engineers, AI designers, developers of evolutionary forms of computation, designers of adaptive systems, etc. The topic overlaps with theoretical biology, developmental psychology and perhaps some aspects of social theory. Just as much of theoretical computer science follows the lead of engineering intuitions and tries to formalise them, there are also some important emerging high level cross disciplinary ideas about natural information processing architectures and evolutionary mechanisms and that can perhaps be unified and formalised in the future. There is some speculation about the evolution of human cognitive architectures and consciousness.

  10. Filename: Sloman_smc98.pdf
    Title: Damasio, Descartes, Alarms and Meta-management
    Author: Aaron Sloman
    Invited contribution to symposium on Cognitive Agents: Modeling Human Cognition,
    at IEEE International Conference on Systems, Man, and Cybernetics
    San Diego, Oct 1998, pp 2652--7.
    Date: 16 Jun 1998


    This paper discusses some of the requirements for the control architecture of an intelligent human-like agent with multiple independent dynamically changing motives in a dynamically changing only partly predictable world. The architecture proposed includes a combination of reactive, deliberative and meta-management mechanisms along with one or more global "alarm" systems. The engineering design requirements are discussed in relation our evolutionary history, evidence of brain function and recent theories of Damasio and others about the relationships between intelligence and emotions. (The paper was completed in haste for a deadline and I forgot to explain why Descartes was in the title. See Damasio 1994.)

  11. Filename: Sloman.toolworkshop.pdf
    Title: What's an AI toolkit for?

    Author: Aaron Sloman
    In proceedings: AAAI-98 Workshop on Software Tools for Developing Agents
    (eds Brian Logan and Jeremy Baxter). July 1998, pp 1-10.
    Date: 20 May 1998 (PDF added 21 Nov 2007)


    This paper identifies a collection of high level questions which need to be posed by designers of toolkits for developing intelligent agents (e.g. What kinds of scenarios are to be developed? What sorts of agent architectures are required? What are the scenarios to be used for? Are speed and ease of development more or less important than speed and robustness of the final system?). It then considers some of the toolkit design options relevant to these issues, including some concerned with multi-agent systems and some concerned with individual intelligent agents of high internal complexity, including human-like agents. A conflict is identified between requirements for exploring new types of agent designs and requirements for formal specification, verifiability and efficiency. The paper ends with some challenges for computer science theorists posed by complex systems of interacting agents.

    Filename: Sloman.toolworkshop.slides.pdf
    Title: Slides for presentation on: What's an AI toolkit for?

    This file contains the slides (two slides per A4 page) prepared for the presentation.

  12. Filename: Sloman.and.Logan.eccm98.pdf
    Title: Architectures and Tools for Human-Like Agents
    In Proceedings 2nd European Conference on Cognitive Modelling,
    Nottingham, April 1-4, 1998. Eds Frank Ritter and Richard M. Young, Nottingham University Press, pp 58--65.
    Authors: Aaron Sloman and Brian Logan

    Date: 11 Mar 1998


    This paper discusses agent architectures which are describable in terms of the "higher level" mental concepts applicable to human beings, e.g. "believes", "desires", "intends" and "feels". We conjecture that such concepts are grounded in a type of information processing architecture, and not simply in observable behaviour nor in Newell's knowledge-level concepts, nor Dennett's "intentional stance." A strategy for conceptual exploration of architectures in design-space and niche-space is outlined, including an analysis of design trade-offs. The SIM_AGENT (SimAgent) toolkit, developed to support such exploration, including hybrid architectures, is described briefly.

  13. Filename: Sloman.oup98.slides.pdf
    Title: Are brains computers?
    Slides prepared for the OUP/Prospect Debate "Are Brains Computers", at LSE, London Nov 19th 1998.

    Other speakers were: Susan Greenfield, Roger Penrose, Dan Robinson, Galen Strawson.)
    Author: Aaron Sloman
    Date: 21 Nov 1998


    A discussion of some of the commonalities between brains and computers as physical systems within which information processing machines can be implemented. Includes a distinction between machines which manipulate energy and forces, machines with manipulate matter and machines which process information. Concludes that we still have much to learn about computers and brains, and although it seems likely that brains are computers we don't yet know what sorts of computers they are.

  14. Filename: CSRP-98-14.pdf
    Title: Qualitative Decision Support using Prioritised Soft Constraints
    Author: Brian Logan and Aaron Sloman
    Technical CSRP-98-14, University of Birmingham School of Computer Science, 1998.
    Date: April 1998


    A key assumption of all problem-solving approaches based on utility theory is that we can assign a utility or cost to each state. This in turn requires that all criteria of interest can be reduced to a common ratio scale. However, many realworld problems are difficult or impossible to formulate in terms of minimising a single criterion, and it is often more natural to express problem requirements in terms of a set of constraints which a solution should satisfy. In this paper, we present a decision support system for route planning in complex terrains based on a novel constraint-based search procedure, A with bounded costs (ABC), which searches for a solution which best satisfies a set of prioritised soft constraints, and illustrate the operation of the system in a simple route planning problem. Our approach provides a means of more clearly specifying problem-solving tasks and more precisely evaluating the resulting solutions as a basis for action.

  15. Filename: Logan.Sloman.etc.CSRP-98-02.pdf
    Title: SIM_AGENT two years on
    Author: B. Logan J. Baxter, R. Hepplewhite and A. Sloman
    (The second and third authors are at DERA Malvern.)
    CSRP-98-02, University of Birmingham School of Computer Science, 1998.
    Date: January 1998


    At ATAL'95 a paper was presented reporting on the SIM AGENT toolkit [8]. SIM AGENT was developed to provide a flexible framework for the exploration of architectures for autonomous agents consisting of a variety of concurrent interacting modules operating in discrete time. The previous paper outlined two early experiments with the toolkit. In this paper, we describe the experiences of two groups actively using the toolkit and report some of what we have learnt about its strengths and weaknesses. We briefly describe how the toolkit has developed since 1995 and sketch some of the ways in which it might be improved.

  16. Filename: Sloman.biota98.html
    Filename: Sloman.biota.slides.pdf

    Title: What sorts of brains can support what sorts of minds?

    Author: Aaron Sloman
    Date: 19 Oct 1998


    The HTML file is the abstract for an invited talk at the DIGITAL BIOTA 2 Conference

    The .ps and .pdf files are postscript and PDF files containing slightly extended versions of the slides I presented at the conference.

  17. Filename: Sloman.twd98.pdf (superseded)
    Filename: (superseded)
    Title: Diagrams in the Mind? (out of date)
    NB: A revised version of this paper appeared in a book published by Springer. The revised version is listed in a later index file in this directory.
    Author: Aaron Sloman
    Invited paper for Thinking With Diagrams conference at Aberystwyth, Aug 1998.
    Date: Aug 1998


    Clearly we can solve problems by thinking about them. Sometimes we have the impression that in doing so we use words, at other times diagrams or images. Often we use both. What is going on when we use mental diagrams or images? This question is addressed in relation to the more general multi-pronged question: what are representations, what are they for, how many different types are they, in how many different ways can they be used, and what difference does it make whether they are in the mind or on paper? The question is related to deep problems about how vision and spatial manipulation work. It is suggested that we are far from understanding what's going on. In particular we need to explain how people understand spatial structure and motion, and I'll try to suggest that this is a problem with hidden depths, since our grasp of spatial structure is inherently a grasp of a complex range of possibilities and their implications. Two classes of examples discussed at length illustrate requirements for human visualisation capabilities. One is the problem of removing undergarments without removing outer garments. The other is thinking about infinite discrete mathematical structures.

  18. Filename: Sloman.consciousness.evolution.pdf
    Title: The evolution of what?

    (Draft very long paper:- Comments welcome)
    Author: Aaron Sloman
    Date: 2 Mar 1998 (DRAFT VERSION)


    There is now a huge amount of interest in consciousness among scientists as well as philosophers, yet there is so much confusion and ambiguity in the claims and counter-claims that it is hard to tell whether any progress is being made. This "position paper" suggests that we can make progress by temporarily putting to one side questions about what consciousness is or which animals or machines have it or how it evolved. Instead we should focus on questions about the sorts of architectures that are possible for behaving systems and ask what sorts of capabilities, states and processes, might be supported by different sorts of architectures. We can then ask which organisms and machines have which sorts of architectures. This combines the standpoint of philosopher, biologist and engineer.

    If we can find a general theory of the variety of possible architectures (a characterisation of "design space") and the variety of environments, tasks and roles to which such architectures are well suited (a characterisation of "niche space") we may be able to use such a theory as a basis for formulating new more precisely defined concepts with which to articulate less ambiguous questions about the space of possible minds.

    For instance our initially ill-defined concept ("consciousness") might split into a collection of more precisely defined concepts which can be used to ask unambiguous questions with definite answers.

    As a first step this paper explores a collection of conjectures regarding architectures and their evolution. In particular we explore architectures involving a combination of coexisting architectural levels including: (a) reactive mechanisms which evolved very early, (b) deliberative mechanisms which evolved later in response to pressures on information processing resources and (c) meta-management mechanisms that can explicitly inspect evaluate and modify some of the contents of various internal information structures.

    It is conjectured that in response to the needs of these layers, perceptual and action subsystems also developed layers, and also that an "alarm" system which initially existed only within the reactive layer may have become increasingly sophisticated and extensive as its inputs and outputs were linked to the newer layers.

    Processes involving the meta-management layer in the architecture could explain the origin of the notion of "qualia". Processes involving the "alarm" mechanism and mechanisms concerned with resource limits in the second and third layers gives us an explanation of three main forms of emotion, helping to account for some of the ambiguities which have bedevilled the study of emotion. Further theoretical and practical benefits may come from further work based on this design-based approach to consciousness.

    A deeper longer term implication is the possibility of a new science investigating laws governing possible trajectories in design space and niche space, as these form parts of high order feedback loops in the biosphere.

    NB This paper is partly superseded by this 2009 paper.

  19. Filename: logan-sloman-aa98poster.pdf
    Title: Cognition and affect: Architectures and tools

    Author: Brian Logan and Aaron Sloman
    Summary of poster presentation. In Proceedings of the Second International Conference on Autonomous Agents (Agents '98), ACM Press, 1998, pp 471--472.
    Date: Feb 1998


    Which agent architectures are capable of justifying descriptions in terms of the 'higher level' mental concepts applicable to human beings? We propose a new kind of architecture-based semantics for mentalistic descriptions in which mental concepts (e.g. 'believes', 'desires', 'intends', 'mood', 'emotion', etc.) are grounded in assumptions about information processing architectures, and not merely in concepts based solely on Dennett's 'intentional stance'. These ideas have led to the design of the SIM_AGENT toolkit which has been used to explore a variety of such architectures.

  20. Filename:
    Filename: Sloman.supervenience.and.implementation.pdf
    Title: Supervenience and Implementation: Virtual and Physical Machines

    Author: Aaron Sloman
    Date: 26 Jan 1998 (DRAFT subject to revision)


    How can a virtual machine $X$ be implemented in a physical machine Y? We know the answer as far as compilers, editors, theorem-provers, operating systems are concerned, at least insofar as we know how to produce these implemented virtual machines, and no mysteries are involved. This paper is about extrapolating from that knowledge to the implementation of minds in brains. By linking the philosopher's concept of supervenience to the engineer's concept of implementation, we can illuminate both. In particular, by showing how virtual machines can be implemented in causally complete physical machines, and still have causal powers, we remove some philosophical problems about how mental processes can be real and can have real effects in the world even if the underlying physical implementation has no causal gaps. This requires a theory of ontological levels.

    This is an extract from a much longer, evolving, paper, in part about the relation between mind and brain, and in part about the more general question of how high level abstract kinds of structures, processes and mechanisms can depend for their existence on lower level, more concrete kinds.

  21. Filename:
    Title: Design Spaces, Niche Spaces and the "Hard" Problem
    (Superseded by IBERAMIA98 paper).
    Author: Aaron Sloman
    Date: 20 Jan 1998 (DRAFT Subject to revision)


    This is an attempt to characterise a new unifying generalisation of the practice of software engineers, AI designers, developers of evolutionary forms of computation, etc. This topic overlaps with theoretical biology, developmental psychology and perhaps some aspects of social theory (yet to be developed!). Much of theoretical computer science follows the lead of engineering intuitions and tries to formalise them. Likewise there are important emerging high level cross disciplinary ideas about processes and architectures found in nature that can be unified and formalised, extending work done in Alife and evolutionary computation. This paper attempts to provide a conceptual framework for thinking about the tasks.

    Within this framework we can also find a new approach to the so-called hard problem of consciousness, based on virtual machine functionalism, and find a new defence for a version of the "Strong AI" thesis.


    The slides begin to apply the ideas developed in the Cognition and Affect project to the analysis of architectural requirements for love and various other emotional and affective states.
    [THE SLIDES ARE PARTLY OUT OF DATE. See Filename: Sloman.kd.pdf (above) ]

  23. Filename: sloman-tucson3.txt
    Title: Architectures and types of consciousness (TUCSON3 Abstract)
    Author: Aaron Sloman
    Date Installed: 15 Jan 2007 (Published 1998)
    This abstract was included in the 'Philosophy' section of the proceedings of this conference: Toward a Science of Consciousness 1998 "Tucson III" April 27-May 2, 1998 Tucson, Arizona All the abstracts are online here.


  24. Filename: Aaron.Sloman.vienna.pdf
    Title: What sort of control system is able to have a personality?
    In Robert Trappl and Paolo Petta (eds), Creating Personalities for Synthetic Actors: Towards Autonomous Personality Agents, Springer (Lecture notes in AI), 1997 pp 166--208,
    (Originally presented at Workshop on Designing personalities for synthetic actors, Vienna, June 1995. Includes some edited transcripts of discussion following presentation.)
    Author: Aaron Sloman

    Date: Installed 24 Jan 1996. Published 1997.

    This paper outlines a design-based methodology for the study of mind as a part of the broad discipline of Artificial Intelligence. Within that framework some architectural requirements for human-like minds are discussed, and some preliminary suggestions made regarding mechanisms underlying motivation, emotions, and personality. A brief description is given of the 'Nursemaid' or 'Minder' scenario being used at the University of Birmingham as a framework for research on these problems. It may be possible later to combine some of these ideas with work on synthetic agents inhabiting virtual reality environments.

    Review of Picard, moved to 1999-02(above).
  25. Logan-Sloman-CSRP-97-30.pdf
    Title: Agent route planning in complex terrains
    Technical report CSRP-97-30, University of Birmingham School of Computer Science, 1997.
    Authors: Brian Logan and Aaron Sloman
    Date: December 1997


    For many autonomous agents, such as mobile robots, autonomous vehicles and Computer Generated Forces, route planning in complex terrain is a critical task, as many of the agent's higher-level goals can only be accomplished if the agent is in the right place at the right time. The route planning problem is often formulated as one of finding a minimum-cost route between two locations in a digitised map which represents a complex terrain of variable altitude, where the cost of a route is an indication of its quality. However route planners which attempt to optimise a single measure of plan quality are difficult to integrate into the architecture of an agent, and the composite cost functions on which they are based are difficult to devise or justify. In this paper, we present a new approach to route planning in complex terrains based on a novel constraint-based search procedure, A with bounded costs (ABC), which generalises the single criterion optimisation problem solved by conventional route planners and describe how a planner based on this approach has been integrated into the architecture of a simple agent. This approach provides a means of more clearly specifying agent tasks and more precisely evaluating the resulting plans as a basis for action.

    Filename: Sloman-ecal97.pdf
    Title: Designing Human-Like Minds
    Unsuccessful submission to ECAL97
    Author: Aaron Sloman
    Date: 3 March 1997

    Under what conditions are "higher level" mental concepts which are applicable to human beings also applicable to artificial agents? Our conjecture is that our mental concepts (e.g. "belief", "desire", "intention", "experience", "mood", "emotion", etc.) are grounded in implicit assumptions about an underlying information processing architecture. At this level mechanisms operate on information structures with semantic content, but there is no presumption of rationality. Thus we don't need to assume Newell's knowledge-level, nor Dennett's "intentional stance." The actual architecture will clearly be richer than that naively presupposed by common sense. We outline a three tiered architecture: with reactive, deliberative and reflective layers, and corresponding layers in perceptual and action subsystems, and discuss some implications.

  26. Filename: Sloman-dfki.pdf
    Title: Architectural Requirements for Autonomous Human-like Agents
    (Slides for a talk at DFKI Saarbruecken, 6th Feb 1997)
    Author: Aaron Sloman

    Date: 6 Feb 1997


    Everybody seems to be talking about agents, though it's not clear when the word "agent" adds anything beyond "system", "program", "tool", etc. My concern is to understand some of the main features of human agency: what they are, how they evolved, how they differ between individuals, how they are implemented, and how far they can be implemented in artificial systems. This is part of the general multi-disciplinary study of "design space", "niche space", their interrelations, and the trajectories possible within these spaces.

    I outline a conjecture that many aspects of human mental functioning, including emotional states, can be explained in terms of an architecture approximately decomposable into three layers, with different evolutionary origins, shared with different animals. The oldest and most widespread is a *reactive* layer. A more recent development, probably shared with fewer animals is a *deliberative* layer. The newest layer is concerned with *meta-management* and may be found only in a few species. The reactive layer involves highly parallel, dedicated and fast mechanisms, capable of fine-tuning but no major structural changes. The deliberative layer involves the ability to create, compare, evaluate, select and act on new complex structures (e.g. plans, solutions to problems, linguistic constructs), a process that requires much stored knowledge and is inherently serial and resource limited, for several different reasons.

    Perceptual and action subsystems had to evolve corresponding layered architectures in order to engage with all these to greatest effect. The third layer is linked to phenomena involving self consciousness and self control (and explains the existence of qualia, as the contents of attentive processes).

    Different sorts of emotional states and processes correspond to different architectural layers, and some of them are likely to arise in sophisticated artificial agents of the future.

    A short introduction is given to the SIM_AGENT toolkit developed in Birmingham for research and teaching activities involving the design of agents each of which has complex interacting internal mechanisms running concurrently, including symbolic and "sub-symbolic" mechanisms. Some of the material overlaps with the Synthetic Minds poster, below.

    Filename: Sloman.and.Logan.agents97.poster.pdf
         (replaced 2-up version 29 Jun 2018)
    Title: Synthetic Minds

    (Poster presented at AA'97 Marina del Rey)
    Authors: Aaron Sloman and Brian Logan
    Date: 4 Feb 1997

    This paper discusses conditions under which some of the "higher level" mental concepts applicable to human beings might also be applicable to artificial agents. The key idea is that mental concepts (e.g. "believes", "desires", "intends", "mood", "emotion", etc.) are grounded in assumptions about information processing architectures, and not merely Newell's knowledge-level concepts, nor concepts based solely on Dennett's "intentional stance."

    Filename: Wright_Sloman_MINDER1.pdf
    Filename: Wright_Sloman_MINDER1.pdf

    Title: MINDER1: An implementation of a protoemotional agent architecture
    Author: Ian Wright, Aaron Sloman
    Type: Technical Report CSRP-97-1
    Date: January 1997
    Institution: University of Birmingham, School of Computer Science
    An implementation of an autonomous resource-bound agent able to operate in a simulated dynamic and complex domain is described. The agent, called MINDER1, is a partial realisation of an architecture for motive processing and attention. It is shown that a global processing state, called perturbance, can emerge from interactions of subcomponents of the architecture. Perturbant states are characteristic features of many states that are commonly called emotional. The agent is compared to other computer simulations of emotional phenomena.


  27. Filename: sloman-actual-possibilities.pdf
    Filename: sloman-actual-possibilities.html
    Title: Actual Possibilities

    Author: Aaron Sloman
    Date: Nov 1996
    in Luigia Carlucci Aiello and Stuart C. Shapiro (eds), Principles of Knowledge Representation and Reasoning: Proceedings of the Fifth International Conference (KR '96), Morgan Kaufmann Publishers, 1996, pp 627-638,


    This is a philosophical 'position paper', starting from the observation that we have an intuitive grasp of a family of related concepts of "possibility", "causation" and "constraint" which we often use in thinking about complex mechanisms, and perhaps also in perceptual processes, which according to Gibson are primarily concerned with detecting positive and negative affordances, such as support, obstruction, graspability, etc. We are able to talk about, think about, and perceive possibilities, such as possible shapes, possible pressures, possible motions, and also risks, opportunities and dangers. We can also think about constraints linking such possibilities. If such abilities are useful to us (and perhaps other animals) they may be equally useful to intelligent artefacts. All this bears on a collection of different more technical topics, including modal logic, constraint analysis, qualitative reasoning, naive physics, the analysis of functionality, and the modelling design processes. The paper suggests that our ability to use knowledge about "de-re" modality is more primitive than the ability to use "de-dicto" modalities, in which modal operators are applied to sentences. The paper explores these ideas, links them to notions of "causation" and "machine", suggests that they are applicable to virtual or abstract machines as well as physical machines. The concept of "possibility-transducer" is introduced. Some conclusions are drawn regarding the nature of mind and consciousness.

  28. Filename: Wright_Sloman_Beaudoin_grief.pdf (PDF searchable since 31 Mar 2013)
    Filename: Wright_Sloman_Beaudoin_grief.html (HTML)
    Filename: Wright_Sloman_Beaudoin_grief.text (Plain text, without diagrams)

    Title: Towards a Design-Based Analysis of Emotional Episodes
    Authors: Ian Wright, Aaron Sloman, Luc Beaudoin

    Date: Oct 1995 (published 1996)

    Appeared (with commentaries) in Philosophy Psychiatry and Psychology, vol 3 no 2, 1996, pp 101--126.

    Journal web site:

    The commentaries, by

    • Dan Lloyd,
    • Cristiano Castelfranchi and Maria Miceli
    • Margaret Boden

    are available here followed by a reply by the authors.

    (This is a revised version of the paper presented to the Geneva Emotions Workshop, April 1995 entitled The Architectural Basis for Grief.)

    The design-based approach is a methodology for investigating mechanisms capable of generating mental phenomena, whether introspectively or externally observed, and whether they occur in humans, other animals or robots. The study of designs satisfying requirements for autonomous agency can provide new deep theoretical insights at the information processing level of description of mental mechanisms. Designs for working systems (whether on paper or implemented on computers) can systematically explicate old explanatory concepts and generate new concepts that allow new and richer interpretations of human phenomena. To illustrate this, some aspects of human grief are analysed in terms of a particular information processing architecture being explored in our research group.

    We do not claim that this architecture is part of the causal structure of the human mind; rather, it represents an early stage in the iterative search for a deeper and more general architecture, capable of explaining more phenomena. However even the current early design provides an interpretative ground for some familiar phenomena, including characteristic features of certain emotional episodes, particularly the phenomenon of perturbance (a partial or total loss of control of attention).

    The paper attempts to expound and illustrate the design-based approach to cognitive science and philosophy, to demonstrate the potential effectiveness of the approach in generating interpretative possibilities, and to provide first steps towards an information processing account of 'perturbant', emotional episodes.

    Many of the architectural ideas have been developed further in later papers and presentations, all available online, e.g.

  29. Filename:
    Title: Towards a general theory of representations
    In Donald Peterson (ed) Forms of representation, Intellect Books, 1996
    Author: Aaron Sloman

    Date: Installed 31 July 1994; Published 1996

    This position paper presents the beginnings of a general theory of representations starting from the notion that an intelligent agent is essentially a control system with multiple control states, many of which contain information (both factual and non-factual), albeit not necessarily in a propositional form. The paper attempts to give a general characterisation of the notion of the syntax of an information store, in terms of types of variation the relevant mechanisms can cope with. Similarly concepts of semantics, pragmatics and inference are generalised to apply to information-bearing sub-states in control systems. A number of common but incorrect notions about representation are criticised (such as that pictures are in some way isomorphic with what they represent).

    This is one of several sequels to the paper presented at IJCAI in 1971

  30. Filename: Sloman.turing90.pdf (PDF)
    Title: Beyond Turing Equivalence
    In: Machines and Thought: The Legacy of Alan Turing (vol I), eds P.J.R. Millican and A. Clark, 1996, OUP(The Clarendon Press) pp 179--219,
    Revised version of paper presented to Turing Colloquium, University of Sussex, 1990.
    Author: Aaron Sloman

    Date: Mon May 8 1995 (Published 1996)


    What is the relation between intelligence and computation? Although the difficulty of defining 'intelligence' is widely recognized, many are unaware that it is hard to give a satisfactory definition of 'computational' if computation is supposed to provide a non-circular explanation for intelligent abilities. The only well-defined notion of 'computation' is what can be generated by a Turing machine or a formally equivalent mechanism. This is not adequate for the key role in explaining the nature of mental processes, because it is too general, as many computations involve nothing mental, nor even processes: they are simply abstract structures. We need to combine the notion of 'computation' with that of 'machine'. This may still be too restrictive, if some non-computational mechanisms prove to be useful for intelligence. We need a theory-based taxonomy of {\em architectures} and {\em mechanisms} and corresponding process types. Computational machines may turn out to be a sub-class of the machines available for implementing intelligent agents. The more general analysis starts with the notion of a system with independently variable, causally interacting sub-states that have different causal roles, including both 'belief-like' and 'desire-like' sub-states, and many others. There are many significantly different such architectures. For certain architectures (including simple computers), some sub-states have a semantic interpretation for the system. The relevant concept of semantics is defined partly in terms of a kind of Tarski-like structural correspondence (not to be confused with isomorphism). This always leaves some semantic indeterminacy, which can be reduced by causal loops involving the environment. But the causal links are complex, can share causal pathways, and always leave mental states to some extent semantically indeterminate.

  31. Filename: Aaron.Sloman.consciousness.lecture.pdf
    Title: A systems approach to consciousness
    (Slides for lecture to RSA London, Feb 1996)
    Author: Aaron Sloman

    Date: Feb 1996

  32. Filename: Aaron.Sloman.rock.pdf (PDF 1996 version)
    HTML version (updated 2017)
    Title: What is it like to be a Rock? (Unpublished)
    Author: Aaron Sloman
    Date: 24 Jan 1996
    This (semi-serious) paper aims to replace deep sounding unanswerable, time-wasting pseudo-questions which are often posed in the context of attacking some version of the strong AI thesis, with deep, discovery-driving, real questions about the nature and content of internal states of intelligent agents of various kinds. In particular the question 'What is it like to be an X?' is often thought to identify a type of phenomenon for which no physical conditions can be sufficient, and which cannot be replicated in computer-based agents. This paper tries to separate out (a) aspects of the question that are important and provide part of the objective characterisation of the states, or capabilities of an agent, and which help to define the ontology that is to be implemented in modelling such an agent, from (b) aspects that are incoherent. The paper supports a philosophical position that is anti-reductionist without being dualist or mystical.

  33. Filename: Sloman.emotions.mit96.slides.pdf
    Title: What sort of architecture can support emotionality?
    (Slides for a talk at MIT Media Lab, Nov 1996. Now out of date.)
    Author: Aaron Sloman

    Date: Nov 1996

    Although much research on emotions is done on other animals (e.g. rats) there seem to be certain characteristically human emotional states which interest poets, novelists, and gossips, such as excited anticipation of an election victory, humiliation at being dismissed. Similar states are inevitable in intelligent robots. Obviously these states involve conceptual abilities not shared by most other mammals. Less obviously, they involve "perturbant" states in which there is partial loss of control of thought processes: you want to prepare that lecture but your mind is drawn back to the source of joy or pain. This presupposes the ability to be in control: you cannot lose what you've never had. The talk contrasts the design-based approach to the study of mind with other approaches. The former involves explorations of "design space", "niche space", and their interconnections. A design-based theory is presented which shows how emotional (perturbant) states are possible.

  34. Filename: Aaron.Sloman.aaai96.cog.pdf
    (Superseded by later paper with same title)
    Title: What sort of architecture is required for a human-like agent?

    Invited talk at Cognitive Modeling Workshop, AAAI96, Portland Oregon, Aug 1996.
    Author: Aaron Sloman

    Date: August 1996


  35. Filename: Aaron.Sloman_Riccardo.Poli_sim_agent_toolkit.pdf
    Title: SIM_AGENT: A toolkit for exploring agent designs
    In Intelligent Agents Vol II (ATAL-95), Eds. Mike Wooldridge, Joerg Mueller, Milind Tambe, Springer-Verlag 1996 pp 392--407.

    Updated version of: Cognitive Science technical report: CSRP-95-3 School of Computer Science, the University of Birmingham.
    Presented at ATAL-95, Workshop on Agent Theories, Architectures, and Languages, at IJCAI-95 Workshop, Montreal, August 1995

    Author: Aaron Sloman and Riccardo Poli
    Date: Oct 1995 version installed here on 7 Jan 1996
    SIM_AGENT is a toolkit that arose out of a project concerned with designing an architecture for an autonomous agent with human-like capabilities. Analysis of requirements showed a need to combine a wide variety of richly interacting mechanisms, including independent asynchronous sources of motivation and the ability to reflect on which motives to adopt, when to achieve them, how to achieve them, and so on. These internal 'management' (and meta-management) processes involve a certain amount of parallelism, but resource limits imply the need for explicit control of attention. Such control problems can lead to emotional and other characteristically human affective states. In order to explore these ideas, we needed a toolkit to facilitate experiments with various architectures in various environments, including other agents. The paper outlines requirements and summarises the main design features of a Pop-11 toolkit supporting both rule-based and 'sub-symbolic' mechanisms. Some experiments including hybrid architectures and genetic algorithms are summarised.

    The toolkit is intended to support exploration of alternative agent architectures rather than to implement a particular agent architecture. It was used in the CogAff project and other projects.

  36. Filename: Sloman.ijcai95.pdf
    Title: A Philosophical Encounter
    This is a four page paper, introducing a panel (John McCarthy, Marvin Minsky, and Aaron Sloman) at IJCAI95 in Montreal August 1995:
    "A philosophical encounter: An interactive presentation of some of the key philosophical problems in AI and AI problems in philosophy."
    John McCarthy also contributed a short paper on interactions between Philosophy and AI, available via his WEB page:
    Author: Aaron Sloman
    Date: 24 April 95
    This paper, along with the following paper by John McCarthy, introduces some of the topics to be discussed at the IJCAI95 event `A philosophical encounter: An interactive presentation of some of the key philosophical problems in AI and AI problems in philosophy.' Philosophy needs AI in order to make progress with many difficult questions about the nature of mind, and AI needs philosophy in order to help clarify goals, methods, and concepts and to help with several specific technical problems. Whilst philosophical attacks on AI continue to be welcomed by a significant subset of the general public, AI defenders need to learn how to avoid philosophically naive rebuttals.
    ijcai95 picture
    `A philosophical encounter: An interactive presentation of some of the key philosophical problems in AI and AI problems in philosophy.'
        Many thanks to Takashi Gomi, at Applied AI Systems Inc, who took the picture.

  37. Filename: Sloman.scai95.pdf
    Title: Exploring design space and niche space
    Invited talk for 5th Scandinavian Conference on AI, Trondheim, May 1995. in Proceedings SCAI95 published by IOS Press, Amsterdam.
    Author: Aaron Sloman
    Date: 16 April 1995
    Most people who give definitions of AI offer narrow views based either on their own work area or the pronouncement of an AI guru about the scope of AI. Looking at the range of research activities to be found in AI conferences, books, journals and laboratories suggests something very broad and deep, going beyond engineering objectives and the study or replication of human capabilities. This is exploration of the space of possible designs for behaving systems (design space) and the relationships between designs and various collections of requirements and constraints (niche space). This exploration is inherently multi-disciplinary, and includes not only exploration of various architectures, mechanisms, formalisms, inference systems, and the like (aspects of natural and artificial designs), but also the attempt to characterise various kinds of behavioural capabilities and the environments in which they are required, or possible. The implications of such a study are profound: e.g. for engineering, for biology, for psychology, for philosophy, and for our view of how we fit into the scheme of things.

  38. Filename: Aaron.Sloman_musings.pdf
    Title: Musings on the roles of logical and non-logical representations in intelligence.
    in: Janice Glasgow, Hari Narayanan, Chandrasekaran, (eds), pp. 7--32
    Diagrammatic Reasoning: Computational and Cognitive Perspectives, AAAI Press 1995
    Author: Aaron Sloman

    Date: Installed 17 October 1994; Published 1995


    This paper offers a short and biased overview of the history of discussion and controversy about the role of different forms of representation in intelligent agents. It repeats and extends some of the criticisms of the `logicist' approach to AI that I first made in 1971, while also defending logic for its power and generality. It identifies some common confusions regarding the role of visual or diagrammatic reasoning including confusions based on the fact that different forms of representation may be used at different levels in an implementation hierarchy. This is contrasted with the way in the use of one form of representation (e.g. pictures) can be {\em controlled} using another (e.g. logic, or programs). Finally some questions are asked about the role of metrical information in biological visual systems.

    This is one of several sequels to the paper presented at IJCAI in 1971

  39. Filename: davis-sloman-poli-aisbq-95.pdf
    Also at
    Title: Simulating agents and their environments,
    In AISB Quarterly, Autumn 1995
    Authors: Darryl Davis, Aaron Sloman and Riccardo Poli,
    Date: 1995


    This paper describes a toolkit that arose out of a project concerned with designing an architecture for an autonomous agent with human-like capabilities. Analysis of requirements showed a need to combine a wide variety of richly interacting mechanisms, including independent asynchronous sources of motivation and the ability to reflect on which motives to adopt, when to achieve them, how to achieve them, and so on. These internal `management' (and metamanagement) processes involve a certain amount of parallelism, but resource limits imply the need for explicit control of attention. Such control problems can lead to emotional and other characteristically human affective states. We needed a toolkit to facilitate exploration of alternative architectures in varied environments, including other agents. The paper outlines requirements and summarises the main design features of a toolkit written in Pop-11. Some preliminary work on developing a multi-agent scenario, using agents of differing sophistication is presented.

    NOTE: See also the current description of the toolkit, here:


  40. Filename: Aaron.Sloman_isre.pdf
    Title: Computational Modelling Of Motive-Management Processes
    "Poster" prepared for the Conference of the International Society for Research in Emotions, Cambridge July 1994 (Final version installed here July 30th 1994)

    Revised version in Proceedings ISRE94, edited by Nico Frijda, ISRE Publications.

    Author: Aaron Sloman, Luc Beaudoin and Ian Wright

    Date: 29 July 1994 (PDF version added 25 Dec 2005)


    This is a 5 page summary with three diagrams of the main objectives and some work in progress at the University of Birmingham Cognition and Affect project. involving: Professor Glyn Humphreys (School of Psychology), and Luc Beaudoin, Chris Paterson, Tim Read, Edmund Shing, Ian Wright, Ahmed El-Shafei, and (from October 1994) Chris Complin (research students). The project is concerned with "global" design requirements for coping simultaneously with coexisting but possibly unrelated goals, desires, preferences, intentions, and other kinds of motivators, all at different stages of processing. Our work builds on and extends seminal ideas of H.A.Simon (1967). We are exploring "broad and shallow" architectures combining varied capabilities most of which are not implemented in great depth. The poster summarises some ideas about management and meta-management processes, attention filtering, and the relevance to emotional states involved "perturbances", where there is partial loss of control of attention.

  41. Filename: Aaron.Sloman_explorations.pdf
    Title: Explorations in Design Space
    in Proc ECAI94, 11th European Conference on Artificial Intelligence Edited by A.G.Cohn, John Wiley, pp 578-582, 1994
    Author: Aaron Sloman

    Date: 20 April 1994


    This paper sketches a vision of AI as a unifying discipline that explores designs for a variety of behaving systems, for both scientific and engineering purposes. This unpacks the idea that AI is the general study of intelligence, whether natural or artificial. Some aspects of the methodology of such a discipline are outlined, and a project attempting to fill gaps in current work introduced. This is one of a series of papers outlining the "design-based" approach to the study of mind, based on the notion that a mind is essentially a sophisticated self-monitoring, self-modifying control system.

    The "design-based" study of architectures for intelligent agents is important not only for engineering purposes but also for bringing together hitherto fragmentary studies of mind in various disciplines, for providing a basis for an adequate set of descriptive concepts, and for making it possible to understand what goes wrong in various human activities and how to remedy the situation. But there are many difficulties to be overcome.

  42. Filename: Aaron.Sloman_representations.control.pdf
    Title: Representations as control substates (DRAFT)

    Author: Aaron Sloman

    Date: March 6th 1994


    (This is a longer, earlier version of "Towards a general theory of representations", and includes some additional material.)
    Since first presenting a paper criticising excessive reliance on logical representations in AI at the second IJCAI at Imperial College London in 1971, I have been trying to understand what representations are and why human beings seem to need so many different kinds, tailored to different purposes. This position paper presents the beginnings of a general answer starting from the notion that an intelligent agent is essentially a control system with multiple control states, many of which contain information (both factual and non-factual), albeit not necessarily in a propositional form. The paper attempts to give a general characterisation of the notion of the syntax of an information store, in terms of types of variation the relevant mechanisms can cope with. Different kinds of syntax can support different kinds of semantics, and serve different kinds of purposes. Similarly concepts of semantics, pragmatics and inference are generalised to apply to information-bearing sub-states in control systems. A number of common but incorrect notions about representation are criticised (such as that pictures are in some way isomorphic with what they represent), and a first attempt is made to characterise dimensions in which forms of representations can differ, including the explicit/implicit dimension.

    This is one of several sequels to the paper presented at IJCAI in 1971

  43. Filename: aaron-sloman-semantics.pdf (PDF)
    Filename: aaron-sloman-semantics.html (HTML)
    Title: Semantics in an intelligent control system
    Invited paper for conference at Royal Society in April 1994 on Artificial Intelligence and the Mind: New Breakthroughs or Dead Ends?
    in Philosophical Transactions of the Royal Society: Physical Sciences and Engineering Vol 349, 1689, pp 43-58, 1994
    With comments by A. Prescott, N. Shadbolt and M. Steedman (not included here).

    This was followed by a paper by Fred Dretske, disagreeing with the claim that AI systems can make use of semantic content.

    Fred Dretske
    (with comments by A. Clark, Y. Wilks, D.Dennett, R.Chrisley, and L.J.Cohen).
    The Explanatory Role of Information pp 59-70
    Author: Aaron Sloman
    Date: May 11 1994 (HTML version added 14 Jun 2015)


    Much research on intelligent systems has concentrated on low level mechanisms or sub-systems of restricted functionality. We need to understand how to put all the pieces together in an architecture for a complete agent with its own mind, driven by its own desires. A mind is a self-modifying control system, with a hierarchy of levels of control, and a different hierarchy of levels of implementation. AI needs to explore alternative control architectures and their implications for human, animal, and artificial minds. Only within the framework of a theory of actual and possible architectures can we solve old problems about the concept of mind and causal roles of desires, beliefs, intentions, etc. The high level "virtual machine" architecture is more useful for this than detailed mechanisms. E.g. the difference between connectionist and symbolic implementations is of relatively minor importance. A good theory provides both explanations and a framework for systematically generating concepts of possible states and processes. Lacking this, philosophers cannot provide good analyses of concepts, psychologists and biologists cannot specify what they are trying to explain or explain it, and psychotherapists and educationalists are left groping with ill-understood problems. The paper sketches some requirements for such architectures, and analyses an idea shared between engineers and philosophers: the concept of "semantic information".

    This is one of several sequels to the paper on representations presented at IJCAI in 1971.

  44. Filename: sim_agent.txt
    Title: Information about the SIM_AGENT toolkit
    Authors: Aaron Sloman and Riccardo Poli
    Date: Originally 1994, updated at intervals since then.
    This is a text file which is part of the online documentation for the SIM_AGENT toolkit. Often referred to subsequently as: SimAgent.
    See also
    (Link to the main SIM_AGENT overview page. Includes pointers to some movies demonstrating simple uses of the toolkit, and also later publications on the toolkit.)

    Also available: November 1994 Seminar Slides. (PDF)
    (Partly out of date.)
    These slides give an early partial descriptions of the sim_agent toolkit implemented in Poplog Pop-11 for exploring architectures for individual or interacting agents. See also the Atal95 paper.


  45. New Searchable HTML version 11 Apr 2014
    Location: (HTML)
    New PDF derived from new HTML:
    Location: (PDF in subdirectory)
    Older version Postscript version originally produced by FrameMaker converted to PDF:

    Title: The Mind as a Control System,

    in Philosophy and the Cognitive Sciences, (eds) C. Hookway and D. Peterson, Cambridge University Press, pp 69-110 1993
    Author: Aaron Sloman

    Date: 1993 (installed) Feb 15 1994

    Originally Presented at Royal Institute of Philosophy conference
    on Philosophy and the Cognitive Sciences,
    in Birmingham in 1992, with proceedings published later.


    Many people who favour the design-based approach to the study of mind, including the author previously, have thought of the mind as a computational system, though they don't all agree regarding the forms of computation required for mentality. Because of ambiguities in the notion of 'computation' and also because it tends to be too closely linked to the concept of an algorithm, it is suggested in this paper that we should rather construe the mind (or an agent with a mind) as a control system involving many interacting control loops of various kinds, most of them implemented in high level virtual machines, and many of them hierarchically organised. (Some of the sub-processes are clearly computational in character, though not necessarily all.) A feature of the system is that the same sensors and motors are shared between many different functions, and sometimes they are shared concurrently, sometimes sequentially. A number of implications are drawn out, including the implication that there are many informational substates, some incorporating factual information, some control information, using diverse forms of representation. The notion of architecture, i.e. functional differentiation into interacting components, is explained, and the conjecture put forward that in order to account for the main characteristics of the human mind it is more important to get the architecture right than to get the mechanisms right (e.g. symbolic vs neural mechanisms). Architecture dominates mechanism

  46. Filename: Aaron.Sloman_variety.formalisms.pdf
    Title: Varieties of Formalisms for Knowledge Representation
    Commentary on: "The Imagery Debate Revisited: A Computational perspective," by Janice I. Glasgow, in: Computational Intelligence. Special issue on Computational Imagery, Vol. 9, No. 4, November 1993
    Author: Aaron Sloman

    Date: Nov 1993


    Whilst I agree largely with Janice Glasgow's position paper, there are a number of relevant subtle and important issues that she does not address, concerning the variety of forms and techniques of representation available to intelligent agents, and issues concerned with different levels of description of the same agent, where that agent includes different virtual machines at different levels of abstraction. I shall also suggest ways of improving on her array-based representation by using a general network representation, though I do not know whether efficient implementations are possible.

    This is one of several sequels to the paper presented at IJCAI in 1971

  47. Filename: Aaron.Sloman_prospects.pdf
    Title: Prospects for AI as the General Science of Intelligence
    in Proceedings AISB93, published by IOS Press as a book:
    Prospects for Artificial Intelligence
    Eds: A.Sloman, D.Hogg, G.Humphreys, D. Partridge, A. Ramsay, Pp: 1--10
    Author: Aaron Sloman
    Date: April 1993


    Three approaches to the study of mind are distinguished: semantics-based, phenomena-based and design-based. Requirements for the design-based approach are outlined. It is argued that AI as the design-based approach to the study of mind has a long future, and pronouncements regarding its failure are premature, to say the least.

  48. Filename: Luc.Beaudoin.and.Sloman_Motive_proc.pdf
    Title: A study of motive processing and attention,
    in A.Sloman, D.Hogg, G.Humphreys, D. Partridge, A. Ramsay (eds) Prospects for Artificial Intelligence, IOS Press, Amsterdam, pp 229-238, 1993.
    Presented at AISB 1993, University of Birmingham.
    Authors: Luc P. Beaudoin and Aaron Sloman
    Date: April 1993


    We outline a design based theory of motive processing and attention, including: multiple motivators operating asynchronously, with limited knowledge, processing abilities and time to respond. Attentional mechanisms address these limits using processes differing in complexity and resource requirements, in order to select which motivators to attend to, how to attend to them, how to achieve those adopted for action and when to do so. A prototype model is under development. Mechanisms include: motivator generators, attention filters, a dispatcher that allocates attention, and a manager. Mechanisms like these might explain the partial loss of control of attention characteristic of many emotional states.


  49. Filename: sloman-prolegomena-communication-affect.pdf (PDF)
    Filename: sloman-prolegomena-communication-affect.html (HTML)
    Author: Aaron Sloman
    Title: Prolegomena to a Theory of Communication and Affect
    In Ortony, A., Slack, J., and Stock, O. (Eds.),
    Communication from an Artificial Intelligence Perspective: Theoretical and Applied Issues.
    Heidelberg, Germany: Springer, 1992, pp 229-260.
    (HTML version added 23 May 2015)

    Paper presented, Nov 1990, to NATO Advanced Research Workshop on "Computational theories of communication and their applications: Problems and Prospects".
    Originally available as Cognitive Science Research Paper, CSRP-91-05, The University of Birmingham.

    Author: Aaron Sloman
    Date: Published 1992 (Presented 1989 at NATO workshop in Italy).


    As a step towards comprehensive computer models of communication, and effective human machine dialogue, some of the relationships between communication and affect are explored. An outline theory is presented of the architecture that makes various kinds of affective states possible, or even inevitable, in intelligent agents, along with some of the implications of this theory for various communicative processes. The model implies that human beings typically have many different, hierarchically organised, dispositions capable of interacting with new information to produce affective states, distract attention, interrupt ongoing actions, and so on. High "insistence" of motives is defined in relation to a tendency to penetrate an attention filter mechanism, which seems to account for the partial loss of control involved in emotions. One conclusion is that emulating human communicative abilities will not be achieved easily. Another is that it will be even more difficult to design and build computing systems that reliably achieve interesting communicative goals.

  50. Filename: sloman-penrose-aij-review.pdf
    Filename: sloman-penrose-aij-review.html
    Title: The Emperor's Real Mind

    Author: Aaron Sloman
    Lengthy review/discussion of Roger Penrose (The Emperor's New Mind) in the journal Artificial Intelligence Vol 56 Nos 2-3 August 1992, pages 355-396
    Author: Aaron Sloman
    Date: 1992
    NOTE ADDED 21 Nov 2009:
    A much shorter review by Aaron Sloman was published in The Bulletin of the London Mathematical Society 24 (1992) 87-96
    Available as PDF and HMTL:
    "The Emperor's New Mind" by Roger Penrose has received a great deal of both praise and criticism. This review discusses philosophical aspects of the book that form an attack on the "strong" AI thesis. Eight different versions of this thesis are distinguished, and sources of ambiguity diagnosed, including different requirements for relationships between program and behaviour. Excessively strong versions attacked by Penrose (and Searle) are not worth defending or attacking, whereas weaker versions remain problematic. Penrose (like Searle) regards the notion of an *algorithm* as central to AI, whereas it is argued here that for the purpose of explaining mental capabilities the *architecture* of an intelligent system is more important than the concept of an algorithm, using the premise that what makes something intelligent is not *what* it does but *how it does it.* What needs to be explained is also unclear: Penrose thinks we all know what consciousness is and claims that the ability to judge Goedel's formula to be true depends on it. He also suggests that quantum phenomena underly consciousness. This is rebutted by arguing that our existing concept of "consciousness" is too vague and muddled to be of use in science. This and related concepts will gradually be replaced by a more powerful theory-based taxonomy of types of mental states and processes. The central argument offered by Penrose against the strong AI thesis depends on a tempting but unjustified interpretation of Goedel's incompleteness theorem. Some critics are shown to have missed the point of his argument. A stronger criticism is mounted, and the relevance of mathematical Platonism analysed. Architectural requirements for intelligence are discussed and differences between serial and parallel implementations analysed.

  51. Filename: sloman-humphreys-jci-proposal.pdf
    Title: Appendix to JCI proposal, The Attention and Affect Project

    Authors: Aaron Sloman and Glyn Humphreys

    Appendix to research grant proposal for the Attention and Affect project. (Paid for computer and computer officer support, and some workshops, for three years, funded by UK Joint Research Council initiative in Cognitive Science and HCI, 1992-1995.)

    Date: January 1992

  52. Filename: Aaron.Sloman_Phenomena.Explain.pdf (PDF)

    Title: What are the phenomena to be explained?

    Author: Aaron Sloman
    Date: Dec 1992

    Seminar notes for the Attention and Affect Project, summarising its long term objectives

  53. Filename: Aaron.Sloman_IP.Emotion.Theory.pdf (PDF)
    Title: Towards an information processing theory of emotions

    Author: Aaron Sloman
    Date: Dec 1992

    Seminar notes for the Attention and Affect Project

  54. Filename: Aaron.Sloman_Silicon.Souls.pdf (PDF)
    Title: Silicon Souls, How to design a functioning mind

    Author: Aaron Sloman

    Date: May 1992

    Professorial Inaugural Lecture, Birmingham, May 1992 In the form of lecture slides for an excessively long lecture. Much of this is replicated in other papers published since.


  55. Filename: BeaudoinSloman-1991-proposalForStudyOfMotiveProcessing.pdf (PDF)
    Title: A Proposal for a Study of Motive Processing

    Authors: Luc Beaudoin and Aaron Sloman
    Date Installed: 30 Jan 2016

    Where published: PhD Thesis proposal Luc Beaudoin, University of Birmingham


    This paper was mostly written by the first author, although it is based on and develops ideas of the second author. The nursemaid scenario was first described by the second author (Sloman, 1986). The first author is in the process of implementing the model described in the paper.

    In this paper we discuss some of the essential features and context of human motive processing, and we characterize some of the state transitions of motives. We then describe in detail a domain for designing an agent exhibiting some of these features. Recent related work is briefly reviewed to demonstrate the need for extending theories to account for the complexities of motive processing described here.

    The nursemaid scenario is available at


  56. Filename: Aaron.Sloman_consciousness.html (HTML)
    Filename: Aaron.Sloman_consciousness.pdf (PDF)
         Installed 27 Dec 2007 -- updated 31 Oct 2015, 6 Nov 2017)
    Title: Notes on consciousness
    Author: Aaron Sloman
    A discussion on why talking about consciousness is premature appeared in AISB Quarterly No 72, pp 8-14, 1990

    Date: Installed circa 1994, Published 1990


    A discussion on why talking about consciousness is premature Appeared in AISB Quarterly No 72, pp 8-14, 1990

    Opening paragraphs:
    {1} The noun "consciousness" as used by most academics (philosophers, psychologists, biologists...) does not refer to anything in particular.

    So you can't sensibly ask how it evolved, or which organisms do and which don't have it.

    Some people imagine they can identify consciousness as "What I've got now". Thinking you can identify what you are talking about by focusing your attention on it is as futile as a Newtonian attempting to identify an enduring portion of space by focusing his attention on it.

    You can identify a portion of space by its relationships to other things, but whether this is or isn't the same bit of space as one identified earlier will depend on WHICH other things you choose: the relationships change over time, but don't all change in unison. Similarly, you can identify a mental state or process by its relationship to other things (e.g. the environment, other mental states or processes, behavioural capabilities, etc), but then whether the same state can or cannot occur in other organisms or machines will depend on WHICH relationships you have chosen -- and there is no uniquely "correct" set of relationships.

    A more recent tutorial presentation on this topic is available here.

    This paper Aaron.Sloman_consciousness.html was modified on 31 Oct 2015 to refer to the discussion of polymorphous concepts, suggesting that "conscious" exhibits parametric polymorphism here:
    6 Nov 2017: Added reference to W. Ross Ashby (1956), An Introduction to Cybernetics as source of the Principle of Requisite Variety.


  57. Filename: (HTML)
    Filename: (PDF)
    Title: On designing a visual system: Towards a Gibsonian computational model of vision.
    In Journal of Experimental and Theoretical AI, 1,4, 289-337 1989

    Author: Aaron Sloman

    Date: 1989, installed here April 18th 1994
    Reformatted, with images included 22 Oct 2006


    This paper contrasts the standard (in AI) "modular" theory of the nature of vision with a more general theory of vision as involving multiple functions and multiple relationships with other sub-systems of an intelligent system. The modular theory (e.g. as expounded by Marr) treats vision as entirely, and permanently, concerned with the production of a limited range of descriptions of visible surfaces, for a central database; while the "labyrinthine" design allows any output that a visual system can be trained to associate reliably with features of an optic array and allows forms of learning that set up new communication channels. The labyrinthine theory turns out to have much in common with J.J.Gibson's theory of affordances, while not eschewing information processing as he did. It also seems to fit better than the modular theory with neurophysiological evidence of rich interconnectivity within and between sub-systems in the brain. Some of the trade-offs between different designs are discussed in order to provide a unifying framework for future empirical investigations and engineering design studies. However, the paper is more about requirements than detailed designs.

    A precursor to this paper was published in 1982 Image interpretation: The way ahead?
    Another was written for a conference in 1986, but has never been formally published: What are the purposes of vision?

  58. Filename:

    Title: Must Intelligent Systems Be Scruffy?

    Presented at Evolving Knowledge Conference. Reading University Sept 1989
    Published in Evolving Knowledge in Natural Science and Artificial Intelligence, Eds J.E.Tiles, G.T.McKee, G.C.Dean, London: Pitman, 1990

    Author: Aaron Sloman

    Date: Presented 1989, Published 1990, Installed here 22 Feb 2002.
    Plain text (troff) version here:


    o Introduction: Neats vs Scruffies
    o The scope of AI
    o Bow to the inevitable: why scruffiness is unavoidable
    o Non-explosive domains
    o The physical (biological, social) world is even harder to deal with
    o Limits of consistency in intelligent systems
    o Scruffy semantics
    o So various kinds of scruffiness are inevitable
    o What should AI do about this?
    o Conclusion

  59. Filename: sloman.pop11.pdf
    Filename: Sloman.pop11.html (HTML Added 17 Jan 2009
    Filename: Sloman.pop11.txt Plain text
    Title: The Evolution of Poplog and Pop-11 at Sussex University
    Originally in POP-11 Comes of Age: The Advancement of an AI Programming Language, (Ed) J.A.D.W. Anderson, Ellis Horwood, pp 30-54, 1989.
    Author: Aaron Sloman
    Date: Originally published 1989. Added here 1 Feb 2001

    This paper gives an overview of the origins and development of the programming language Pop-11, one of the Pop family of languages including Pop1, Pop2, Pop10, Wpop, Alphapop. Pop-11 is the msot sophisticated version, comparable in scope and power to Common Lisp, though different in many significant details, including its syntax. For more on Pop-11 and Poplog, the system of which it is the core language, see:

    This paper first appeared in a collection published in 1989 to celebrate the 21st birthday of the Pop family of languages.


  60. Filename: sloman-dennett-bbs-1987.pdf
    Title: Why Philosophers Should be Designers
    (BBS Commentary on Dennett's Intentional Stance)

    Authors: Aaron Sloman
    Date Installed: 9 Sep 2009
    Date Published: 1988

    Where published:

    Behavioral and Brain Sciences (BBS) 1988, 11 (3): p529-530.

    Commentary on:
    Dennett, D.C. Precis of The Intentional Stance.
    BBS 1988 11 (3): 495-505.


    This is a short commentary on some aspects of D.C.Dennett's book 'The Intentional Stance'. The paper criticises the "intentional stance" as not providing real insight into the nature of intelligence because it ignores the question HOW behaviour is produced. The paper argues that only by taking the "design stance" can we understand the difference between intelligent and unintelligent ways of doing the same thing.

  61. Title: How to dispose of the free will issue
    NOTE (2 May 2014):
    A revised slightly extended and reformatted version of the paper is now available (HTML and PDF) here:
    Filename: sloman-freewill-1988.html (HTML)
    Filename: sloman-freewill-1988.pdf (PDF)

    Filename: Aaron.Sloman_freewill.pdf (Old version)

    Author: Aaron Sloman
    Date: 1988 (or earlier)
    Originally posted to circa 1988.
    A similar version appeared in AISB Quarterly, Winter 1992/3, Issue 82, pp. 31-2.

    An improved, elaborated, version of this paper with different sub-headings by Stan Franklin was published as Chapter 2 of his book Artificial Minds (MIT Press, 1995).
    Paper back version available.)
    Franklin's Chapter is also available on this web site, with his permission:


    Much philosophical discussion concerning freedom of the will is based on an assumption that there is a well-defined distinction between systems whose choices are free and those whose choices are not. This assumption is refuted by showing that when requirements for behaving systems are considered there are very many design options which correspond to a wide variety of distinctions more or less closely associated with our naive ideas of individual freedom. Thus, instead of one major distinction there are many different distinctions; different combinations of design choices will produce different sorts of agents, and the naive distinction is not capable of classifying them. In this framework, the pre-theoretical concept of freedom of the will needs to be abandoned and replaced with a host of different technical concepts corresponding to the capabilities enabled by different designs.

    It is argued that biological evolution "discovered" many of the design options and produced more and more complex combinations of increasingly sophisticated designs giving animals more and more freedom (though all the interesting varieties depend on the operation of deterministic mechanisms).
    See also section 10.13 of Chapter 10 of The Computer Revolution in Philosophy: Philosophy, science and models of mind (1978) .
    Added (2006): Four Concepts of Freewill: Two of them incoherent
    This argues that people who discuss problems of free will often talk past each other because they do not clearly perceive that there is not one universally accepted notion of "free will". Rather there are at least four, only two of which are of real value.

  62. Filename: jam-tomorrow-duboulay-sloman.html (HTML)
    Filename: jam-tomorrow-duboulay-sloman.pdf (PDF)

    Title: Bread today, jam tomorrow: The impact of AI on education

    Authors: Benedict du Boulay and Aaron Sloman
    Date Installed here: 23 Feb 2016

    Where published: Fifth International Conference on Technology and Education
    Education In The 90s: Challenges Of The New Information Technologies
    Edinburgh, Scotland 28 - 31 March 1988

    Also here (but no longer available):

    Cognitive Science Research Papers
    Serial No. CSRP 098
    School of Cognitive Sciences
    University of Sussex
    Brighton, BN1 9QN, England


    Several factors make it very difficult to automate skilled teacher student interactions, e.g. integrating new material in a way that links effectively to the student's existing knowledge, taking account of the student's goals and beliefs and adjusting the form of presentation as appropriate. These difficulties are illustrated with examples from teaching programming. There are domain-specific and domain-neutral problems in designing ITS. The domain-neutral problems include: encyclopaedic knowledge, combining different kinds of knowledge, knowing how to devise a teaching strategy, knowing how to monitor and modify the strategy, knowing how to motivate intellectual curiosity, understanding the cognitive states and processes involved in needing (wanting) or an explanation, knowing how to cope with social and affective processes, various communicative skills (this includes some of the others), knowing how to use various representational and communicative media, and knowing when to use them (an example of strategy).


  63. Filename: Aaron.Sloman_Motives.Mechanisms.pdf (PDF added 3 Jan 2010)
    Filename: Aaron.Sloman_Motives.Mechanisms.txt
    Title: Motives Mechanisms and Emotions
    Author: Aaron Sloman
    In Cognition and Emotion 1,3, pp.217-234 1987,
    reprinted in M.A. Boden (ed) The Philosophy of Artificial Intelligence, "Oxford Readings in Philosophy" Series Oxford University Press, pp 231-247 1990.
    (Also available as Cognitive Science Research Paper No 62, Sussex University.)

    Abstract: (From the introduction)

    Ordinary language makes rich and subtle distinctions between different sorts of mental states and processes such as mood, emotion, attitude, motive, character, personality, and so on. Our words and concepts have been honed for centuries against the intricacies of real life under pressure of real needs and therefore give deep hints about the human mind.

    Yet actual usage is inconsistent, and our ability to articulate the distinctions we grasp and use intuitively is as limited as our ability to recite rules of English syntax. Words like "motive" and "emotion" are used in ambiguous and inconsistent ways. The same person will tell you that love is an emotion, that she loves her children deeply, and that she is not in an emotional state. Many inconsistencies can be explained away if we rephrase the claims using carefully defined terms. As scientists we need to extend colloquial language with theoretically grounded terminology that can be used to mark distinctions and describe possibilities not normally discerned by the populace. For instance, we'll see that love is an attitude, not an emotion, though deep love can easily trigger emotional states. In the jargon of philosophers (Ryle 1949), attitudes are dispositions, emotions are episodes, though with dispositional elements.

    For a full account of these episodes and dispositions we require a theory about how mental states are generated and controlled and how they lead to action -- a theory about the mechanisms of mind. The theory should explain how internal representations are built up, stored, compared, and used to make inferences, formulate plans or control actions. Outlines of a theory are given below. Design constraints for intelligent animals or machines are sketched, then design solutions are related to the structure of human motivation and to computational mechanisms underlying familiar emotional states.

    Emotions are analysed as states in which powerful motives respond to relevant beliefs by triggering mechanisms required by resource-limited intelligent systems. New thoughts and motives get through various filters and tend to disturb other ongoing activities. The effects may interfere with or modify the operation of other mental and physical processes, sometimes fruitfully sometimes not. These are states of being "moved". Physiological changes need not be involved. Emotions contrast subtly with related states and processes such as feeling, impulse, mood, attitude, temperament; but there is no space for a full discussion here.


  64. Filename: sloman-searle-85.html
    Filename: sloman.searle.85.pdf
    Filename: sloman.searle.85.text

    Title: Did Searle attack strong strong or weak strong AI?

    Originally in
    A.G. Cohn and J.R. Thomas (eds) Artificial Intelligence and Its Applications, John Wiley and Sons 1986.
    (Proceedings AISB Conference, Warwick University, 1985)
    Author: Aaron Sloman

    Date: 1986 (Installed here 13 Jan 2001 (Originally presented 1985)
    (Added HTML version 22 May 2015)
    (Added Postscript and PDF versions 23 Oct 2005)


    John Searle's attack on the Strong AI thesis, and the published replies, are all based on a failure to distinguish two interpretations of that thesis, a strong one, which claims that the mere occurrence of certain process patterns will suffice for the occurrence of mental states, and a weak one which requires that the processes be produced in the right sort of way. Searle attacks strong strong AI, while most of his opponents defend weak strong AI. This paper explores some of Searle's concepts and shows that there are interestingly different versions of the 'Strong AI' thesis, connected with different kinds of reliability of mechanisms and programs.

    Keywords: Searle, strong AI, minds and machines, intentionality, meaning, reference, computation.

  65. Filename: Sloman.ecai86.pdf
    Title: Reference without causal links,
    In Proceedings 7th European Conference on Artificial Intelligence, Brighton, July 1986. Re-printed in
    J.B.H. du Boulay, D.Hogg, L.Steels (eds) Advances in Artificial Intelligence - II North Holland, 369-381, 1987.
    Author: Aaron Sloman

    Date: 1986


    This enlarges on earlier work attempting to show in a general way how it might be possible for a machine to use symbols with `non-derivative' semantics. It elaborates on the author's earlier suggestion that computers understand symbols referring to their own internal `virtual' worlds. A machine that grasps predicate calculus notation can use a set of axioms to give a partial, implicitly defined, semantics to non-logical symbols. Links to other symbols defined by direct causal connections within the machine reduce ambiguity. Axiom systems for which the machine's internal states do not form a model give a basis for reference to an external world without using external sensors and motors.

  66. Filename: vision-purposes-sloman.pdf (PDF)
    Title: What are the purposes of vision?
    Based on invited presentation at Fyssen Foundation Workshop on Vision,
    Versailles France, March 1986, Organiser: M. Imbert
    (The proceedings were never published.)
    Author: Aaron Sloman
    Date written: approx 1986
    Date Installed: 8 Oct 2012


     1 Introduction
     2 The `modular' theory
     3 Previous false starts
     4 What is, what should be, and what could be
     5 Problems with the modular model
     6 Higher level principles
     7 Is this a trivial verbal question?
     8 Interpretation involves "conceptual creativity"
     9 The biological need for conceptual creativity
    10 The uses of a visual system
    11 Sub-tasks for vision in executing plans
    12 Perceiving functions and potential for change
    13 Figure and ground
    14 Seeing why
    15 Seeing spaces
    16 Seeing mental states
    17 Practical uses of 2-D image information
    18 Varieties of descriptive databases
    19 Kinds of visual learning
    20 What changes during visual learning?
    21 Triggering mental processes
    22 The enhanced model
    23 Conclusion: a three-pronged objective
    24 Acknowledgment
    25 References
    At the Fyssen workshop I tried to initiate a discussion of the functions (or
    purposes, or uses) of vision in humans and other animals. However, the others
    present all seemed to assume that it was clear what the functions were, and they
    wished to discuss mechanisms that could explain those functions. However, that
    usually requires adopting a restricted view of animal vision, or even future robot
    This paper outlines some of the diversity of functions of vision in animals, and
    future robots, and begins a discussion of the variety of architectures, forms of
    representation and mechanisms that could be useful in visual systems in various
    contexts. There is still a huge amount to be done.
    This paper extends ideas in Chapters 6 to 10 of The Computer Revolution in Philosophy
    and in Image interpretation: The way ahead? Some of the ideas were also included
    in the 1989 paper on vision "On designing a visual system: Towards a Gibsonian computational model of vision."


  67. Filename: Sloman.ijcai85.pdf
    Title: What enables a machine to understand?
    In Proceedings 9th International Joint Conference on AI, pp 995-1001, Los Angeles, August 1985.
    Author: Aaron Sloman

    Date: 1985


    The 'Strong AI' claim that suitably programmed computers can manipulate symbols that THEY understand is defended, and conditions for understanding discussed. Even computers without AI programs exhibit a significant subset of characteristics of human understanding. To argue about whether machines can REALLY understand is to argue about mere definitional matters. But there is a residual ethical question.

  68. Filename: Aaron.Sloman_Rep.Formalisms.pdf
    Title: Why we need many knowledge representation formalisms,
    In Research and Development in Expert Systems, ed. M Bramer, pp 163-183, Cambridge University Press 1985.
    (Proceedings Expert Systems 85 conference. Also Cognitive Science Research paper No 52, Sussex University.)
    Author: A.Sloman

    Date: 1985 (Reformatted December 2005)


    Against advocates of particular formalisms for representing ALL kinds of knowledge, this paper argues that different formalisms are useful for different purposes. Different formalisms imply different inference methods. The history of human science and culture illustrates the point that very often progress in some field depends on the creation of a specific new formalism, with the right epistemological and heuristic power. The same has to be said about formalisms for use in artificial intelligent systems. We need criteria for evaluating formalisms in the light of the uses to which they are to be put. The same subject matter may be best represented using different formalisms for different purposes, e.g. simulation vs explanation. If different notations and inference methods are good for different purposes, this has implications for the design of expert systems.

    This is one of several sequels to the paper presented at IJCAI in 1971

  69. Filename: sloman-realtime-bcs86.pdf
    Title: Real Time Multiple-Motive Expert Systems
    In Real time multiple-motive expert systems, Proceedings Expert Systems 1985,
    Ed. M. Merry, Cambridge University Press, 1985, pp. 213--224.

    A sequel to Sloman and Croucher 1981 (Why robots will have emotions)

    Author: Aaron Sloman

    Date: 1985 (Installed here May 2004).


    Sooner or later attempts will be made to design systems capable of dealing with a steady flow of sensor data and messages, where actions have to be selected on the basis of multiple, not necessarily consistent, motives, and where new information may require substantial re-evaluation of plans and strategies, including suspension of current actions. Where the world is not always friendly, and events move quickly, decisions will often have to be made which are time-critical. The requirements for this sort of system are not clear, but it is clear that they will require global architectures very different from present expert systems or even most AI programs. This paper attempts to analyse some of the requirements, especially the role of macroscopic parallelism and the implications of interrupts. It is assumed that the problems of designing various components of such a system will be solved, e.g. visual perception, memory, inference, planning, language understanding, plan execution, etc. This paper is about some of the problems of putting them together, especially perception, decision-making, planning and plan-execution systems.

  70. Filename: sloman-popper-3-worlds.pdf

    Title: A Suggestion About Popper's Three Worlds In the Light of Artificial Intelligence
    (Previously: Artificial Intelligence and Popper's Three Worlds)

    Author: Aaron Sloman

    Date: 1985
    Date Installed: 9 Oct 2012

    Where published:

    In Problems, Conjectures, and Criticisms: New Essays in Popperian Philosophy,
    Eds. Paul Levinson and Fred Eidlin, Special issue of ETC: A Review of General Semantics, (42:3) Fall 1985.


    Materialists claim that world2 is reducible to world1. Work in Artificial Intelligence suggests that world2 is reducible to world3, and that one of the main explanatory roles Popper attributes to world2, namely causal mediation between worlds 1 and 3, is a redundant role. The central claim can be summed up as: "Any intelligent ghost must contain a computational machine." Computation is a world3 process. Moreover, much of AI (like linguistics) is clearly both science and not empirically refutable, so Popper's demarcation criterion needs to be replaced by a criterion which requires scientific theories to have clear and definite consequences concerning what is possible, rather than about what will happen.


  71. Filename: sloman-space-of-minds-84.pdf
    Filename: sloman-space-of-minds-84.html (HTML)
    Title: The structure of the space of possible minds

    Author: Aaron Sloman
    Originally published in The Mind and the Machine: philosophical aspects of Artificial Intelligence,
    ed. Stephen Torrance, Ellis Horwood, 1984, pp 35-42.
    Date Installed: 13 Jan 2007 (Originally published 1984)

    Abstract: (Extract from text)

    Describing this structure is an interdisciplinary task I commend to philosophers. My aim for now is not to do it -- that's a long term project -- but to describe the task. This requires combined efforts from several disciplines including, besides philosophy: psychology, linguistics, artificial intelligence, ethology and social anthropology.

    Clearly there is not just one sort of mind. Besides obvious individual differences between adults there are differences between adults, children of various ages and infants. There are cross-cultural differences. There are also differences between humans, chimpanzees, dogs, mice and other animals. And there are differences between all those and machines. Machines too are not all alike, even when made on the same production line, for identical computers can have very different characteristics if fed different programs. Besides all these existing animals and artefacts, we can also talk about theoretically possible systems.

    This theme was taken up by (among others)
    Roman V. Yampolskiy, The Universe of Minds (2014)

  72. Filename: sloman.beginners.pdf (PDF)
    Filename: sloman.beginners.html (HTML)
    Title: Beginners need powerful systems
    Originally in New Horizons in Educational Computing (Ed) M. Yazdani,
    Ellis Horwood, 1984. pp 220-235
    Author: Aaron Sloman
    Date: Originally published 1984. Added here 27 Nov 2001


    The paper argues that instead of choosing very simple and restricted programming languages and environments for beginners, we can offer them many advantages if we use powerful, sophisticated languages, libraries, and development environments. Several reasons are given. The Pop-11 subset of the Poplog system is offered as an example.

    The ideas are developed further in the description of teaching resources in Poplog
    And in my presentation at the award of an Honorary DSc at the University of Sussex in 2006

  73. Filename: sloman-computational-mind.pdf (PDF)
    Title: Towards a Computational Theory of Mind,
    Originally in Artificial Intelligence - Human Effects, (Eds) M. Yazdani and A. Narayanan,
    Ellis Horwood, Chichester, 1984. pp 173--182
    Author: Aaron Sloman
    Date: Originally published 1984. Added here 7 Aug 2012
    New End-Note added 8 Aug 2012


    (From the introduction to the chapter.)
    Cognitive Science has three interrelated aspects: theoretical, applied and empirical. Work in all three areas depends on and feeds back into the other two. Theoretical work explores possible computational systems, possible mental processes and structures, attempting to understand what sorts of mechanisms and representational systems are possible, how they differ, what their strengths and weaknesses are, etc. Empirical work studies existing intelligent systems, e.g. humans and other animals. Applied work is both concerned with problems relating to existing minds (e.g. learning difficulties, psychopathology) and also the design of new useful computational systems. This paper sketches some of the assumptions underlying much of the theoretical work, and hints at some of the practical applications. In particular, education and psychotherapy are both activities in which the computational processes in the mind of the pupil or patient are altered. In order to understand what they are doing, educationalists and psychotherapists require a computational theory of mind. This is not the dehumanising notion it may at first appear to be.


  74. Filename: imageinterpretation.pdf (OCR version reformatted: 280 KB PDF)
    Filename: image-interp-way-ahead.pdf (Scanned original pages: 10MB PDF)
    Title: Image interpretation: The way ahead?
    Invited talk, originally published in
    Physical and Biological Processing of Images
    (Proceedings of an international symposium organised by The Rank Prize Funds, London, Sept 1982.)
    Editors: O.J.Braddick and A.C. Sleigh.
    Pages 380--401, Springer-Verlag, 1983.
    Author: Aaron Sloman
    Date Installed: 25 Oct 2006 (Originally written 1982)
    Some unsolved problems about vision are discussed in relation to the goal of understanding the space of possible mechanisms with the power of human vision. The following issues are addressed: What are the functions of vision? What needs to be represented? How should it be represented? What is a good global architecture for a human like visual system? How should the visual sub-system relate to the rest of an intelligent system? It is argued that there is much we do not understand about the representation of visible structures, the functions of a visual system and its relation to the rest of the human mind. Some tentative positive suggestions are made, but more questions are offered than answers.

    This paper is available in two formats as explained above. The OCR version probably has some errors that I have not corrected. But it is much smaller and easier to read than the scanned in images. I had forgotten about this paper for many years, until I stumbled across a reference to it. It is a precursor to
    On designing a visual system: Towards a Gibsonian computational model of vision.
    (Published in 1989).

    The 1982 paper presents several of the ideas I later developed in the context of a more embracing theory of the architecture of human-like minds, in which there are concurrently active 'layers' of different kinds performing different tasks, some evolutionarily very old some newer, all sharing the same sensors and effectors (see also 'The mind as a control system'(1993)).

    I believe this is potentially a far more powerful and general theory than the much discussed 'dual-stream' or 'dual-pathway' theories of vision based on differences between dorsal and ventral visual pathways. But evaluating the ideas requires a much broader multi-disciplinary perspective, which is not easy for researchers to achieve.

    This paper pointed out, among other things, the need for natural and artificial vision systems to be able to perceive both static and continuously moving structures, and structures with parts that change their shapes and relationships continuously. It also emphasised differences between seeing what is the case and seeing how to do something, especially in a changing situation, involving continuous control of movement (e.g. painting a chair).

    It later turned out that this distinction, which is familiar to engineers as a distinction between use of vision to acquire and record information that might be used for variety of purposes and use of vision for 'servo-control', was loosely related to distinct functions of ventral and dorsal visual pathways in primate brains, which were misleadingly labelled "what" and "where" pathways by some researchers, who later attempted to correct the confusion was made by renaming these "perception" and "action" pathways, which unfortunately does not allow visual control of actions to be termed "perception" or "seeing". These confusions are still wide-spread.

  75. Filename: sloman-on-boden-1983.pdf
    Title: Commentary on Boden on "Artificial Intelligence and Animal Psychology"

    Author: Aaron Sloman
    Date Published: 1983 (Date Installed: 16 Dec 2008)

    Where published:

    New Ideas in Psychology
    vol. 1, no = 1 pp. 41--50. Online here
    Abstract: (Introduction to article)
    Having discussed these issues with the author over many years, I was not surprised to find myself agreeing with nearly everything in the paper, and admiring the clarity and elegance of its presentation. All I can offer by way of commentary, therefore, is a collection of minor quibbles, some reformulations to help readers for whom the computational approach is very new, and a few extensions of the discussion.

    I'll start with a few explanatory comments on the nature of A.I., to supplement the section of the paper "A.I. as the Study of Representation". Cognitive Science has three main classes of goals (a) theoretical (the study of possible minds, possible forms of representation and computation), (b) empirical (the study of actual minds and mental abilities of humans and other animals), (c) practical (the attempt to help individuals and society by alleviating problems (i.e. learning problems, mental disorders) and designing new useful intelligent machines).

    Activities pursuing these three goals are most fruitful when the goals are interlinked, providing opportunities for feedback between theoretical, empirical and applied work. Artificial Intelligence is a subdiscipline of Cognitive Science which straddles the theoretical approach (studying general properties of possible computational systems) and applications (designing new systems to help in education, industry, commerce, medicine, entertainment). Its empirical content is mostly based not on specialised research, but on common knowledge of many of the things people can do - such as using and understanding language, seeing things, making plans, solving problems, playing games. This knowledge of what people can do sets design goals for both the theoretical and the applied work. In particular, an important aspect of A.I. research is task analysis: given that people can perform a certain task, what are the computational resources required, and what are the trade-offs between different representations and processing strategies? This sort of analysis is relevant to the study of other animals insofar as many human abilities are shared with other animals.

  76. Filename: sloman-ijcai83-meaning.html
    Filename: sloman-ijcai83-meaning.pdf
    Title: Introduction to Panel Discussion: Under What Conditions Can A Machine Attribute Meanings To Symbols?

    Authors:Aaron Sloman, et al.,
    Date: 1983 (Installed here 23 Mar 2011)

    Where published:

    Aaron Sloman, Drew V. McDermott, William A. Woods, Brian Cantwell Smith and Patrick J. Hayes,
    "Panel discussion: Under What Conditions Can a Machine Attribute Meanings to Symbols?", chaired by Aaron Sloman,
    In Proceedings IJCAI 1983, pp44-48,

  77. Filename: sloman-aslib83.pdf
    Title: An Overview Of Some Unsolved Problems In Artificial Intelligence

    Author: Aaron Sloman
    Date: 1983 (installed here 19 Mar 2012)

    Where published:

    Intelligent Information Retrieval: Informatics 7, 1983 (pp.3--14)
    Ed. Kevin P. Jones
    Proceedings Cambridge Aslib Informatics 7 Conference, Cambridge 22-23 March 1983.

    Abstract (Extract from Introduction):

    It is rash for the first speaker at a conference to offer to talk about unsolved problems: the risk is that subsequent papers will present solutions. To minimise this risk, I resolved to discuss only some of the really hard long term problems. Consequently, I'll have little to say about solutions!

    These long-term problems are concerned with the aim of designing really intelligent systems. Of course, it is possible to quibble endlessly about the definition of 'intelligent', and to argue about whether machines will ever really be intelligent, conscious, creative, etc. I want to by-pass such semantic debates by indicating what I understand by the aim of designing intelligent machines. I shall present a list of criteria which I believe are implicitly assumed by many workers in Artificial Intelligence to define their long term aims. Whether these criteria correspond exactly to what the word 'intelligent' means in ordinary language is an interesting empirical question, but is not my present concern. Moreover, it is debatable whether we should attempt to make machines which meet these criteria, but for present purposes I shall take it for granted that this is a worthwhile enterprise, and address some issues about the nature of the enterprise.

    Finally, it is not obvious that it is possible to make artefacts meeting these criteria. For now I shall ignore all attempts to prove that the goal is unattainable. Whether it is attainable or not, the process of attempting to design machines with these capabilities will teach us a great deal, even if we achieve only partial successes.


  78. Filename: Sloman.emot.gram.pdf
    Title: Towards a Grammar of Emotions,

    in New Universities Quarterly, 36,3, pp 230-238, 1982.
    Author: Aaron Sloman
    Date: Installed here 6 Dec 1998 (Originally Published in 1982)


    By analysing what we mean by 'A longs for B', and similar descriptions of emotional states we see that they involve rich cognitive structures and processes, i.e. computations. Anything which could long for its mother, would have to have some sort of representation of its mother, would have to believe that she is not in the vicinity, would have to be able to represent the possibility of being close to her, would have to desire that possibility, and would have to be to some extent pre-occupied or obsessed with that desire. The paper includes a fairly detailed discussion of what it means to say 'X is angry with Y', and relationships between anger, exasperation, annoyance, dismay, etc., including exploring some of the dynamics of emotions such as anger. Emotions are contrasted with attitudes and moods.
    This paper contains examples of the technique of conceptual analysis explained in a tutorial that formed Chapter 4 of The Computer Revolution in Philosophy (1978)
    That chapter is available as part of the new online edition of the book:

  79. Filename: comp-epistemology-sloman.pdf
    Title: Computational Epistemology

    in Genetic epistemology and cognitive science Structures and cognitive processes:
    Proceedings of the 2nd and 3rd Advanced Courses in Genetic Epistemology,
    organised by the Fondation Archives Jean Piaget in 1980 and 1981. - Geneva: Fondation Archives Jean Piaget, 1982. - P. 49-93.

    Author: Aaron Sloman

    Date: (Originally Published in 1982)


    To be added.


  80. Filename: skills-cogsci-81.html (HTML)
    Filename: skills-cogsci-81.pdf (PDF)
    Filename: skills-cogsci-81.txt (Plain Text)
    Title: Skills, Learning and Parallelism

    In Proceedings 3rd Cognitive Science Conference, Berkeley, 1981. pp 284-5.
    Author: Aaron Sloman
    Date installed here: 15 Jan 2008 (Written April 1981)
    Note: The conference schedule is available here: cogsci-1981-Berkeley-programme.pdf

    Abstract: (Extract from the text)

    The distinction between compiled and interpreted programs plays an important role in computer science and may be essential for understanding intelligent systems. For instance programs in a high-level language tend to have a much clearer structure than the machine code compiled equivalent, and are therefore more easily synthesised, debugged and modified. Interpreted languages make it unnecessary to have both representations. Further, if the interpreter is itself an interpreted program it can be modified during the course of execution, for instance to enhance the semantics of the language it is interpreting, and different interpreters may be used with the same program, for different purposes: e.g. an interpreter running the program in 'careful mode' would make use of comments ignored by an interpreter running the program at maximum speed (Sussman 1975). (The possibility of changing interpreters vitiates many of the arguments in Fodor (1975) which assume that all programs are compiled into a low level machine code, whose interpreter never changes).

    People who learn about the compiled/interpreted distinction frequently re-invent the idea that the development of skills in human beings may be a process in which programs are first synthesised in an interpreted language, then later translated into a compiled form. The latter is thought to explain many features of skilled performance, for instance, the speed, the difficulty of monitoring individual steps, the difficulty of interrupting, starting or resuming execution at arbitrary desired locations, the difficulty of modifying a skill, the fact that performance is often unconscious after the skill has been developed, and so on. On this model, the old jokes about centipedes being unable to walk, or birds to fly, if they think about how they do it, might be related to the impossibility of using the original interpreter after a program has been compiled into a lower level language.

    Despite the attractions of this theory I suspect that a different model is required in some cases.

  81. Filename: sloman-croucher-warm-heart.pdf
    Title: You don't need a soft skin to have a warm heart: Towards a computational analysis of motives and emotions.

    Authors: Aaron Sloman and Monica Croucher

    Originally a Cognitive Science Research Paper at Sussex University:
    Sloman, Aaron and Monica Croucher, "You don't need a soft skin to have a warm heart: towards a computational analysis of motives and emotions," CSRP 004, 1981.
    Date Installed: 17 Jun 2005. Re-formatted: 11 Mar 2018
    (Written circa 1980-81, at Sussex University. CSRP 004, 1981)


    The paper introduces an interdisciplinary methodology for the study of minds of animals humans and machines, and, by examining some of the pre-requisites for intelligent decision-making, attempts to provide a framework for integrating some of the fragmentary studies to be found in Artificial Intelligence.

    The space of possible architectures for intelligent systems is very large. This essay takes steps towards a survey of the space, by examining some environmental and functional constraints, and discussing mechanisms capable of fulfilling them. In particular, we examine a subspace close to the human mind, by illustrating the variety of motives to be expected in a human-like system, and types of processes they can produce in meeting some of the constraints.

    This provides a framework for analysing emotions as computational states and processes, and helps to undermine the view that emotions require a special mechanism distinct from cognitive mechanisms. The occurrence of emotions is to be expected in any intelligent robot or organism able to cope with multiple motives in a complex and unpredictable environment.

    Analysis of familiar emotion concepts (e.g. anger, embarrassment, elation, disgust, pity, etc.) shows that they involve interactions between motives (e.g. wants, dislikes, ambitions, preferences, ideals, etc.) and beliefs (e.g. beliefs about the fulfilment or violation of a motive), which cause processes produced by other motives (e.g. reasoning, planning, execution) to be disturbed, disrupted or modified in various ways (some of them fruitful). This tendency to disturb or modify other activities seems to be characteristic of all emotions. In order fully to understand the nature of emotions, therefore, we need to understand motives and the types of processes they can produce.

    This in turn requires us to understand the global computational architecture of a mind. There are several levels of discussion: description of methodology, the beginning of a survey of possible mental architectures, speculations about the architecture of the human mind, analysis of some emotions as products of the architecture, and some implications for philosophy, education and psychotherapy.

  82. Filename: Aaron.Sloman_why_robot_emotions.pdf
    Title: Why robots will have emotions
    Authors: Aaron Sloman and Monica Croucher

    Date: August 1981 (Installed in this directory 10 Nov 1994)
    Originally appeared in Proceedings IJCAI 1981, Vancouver
    Also available from Sussex University as Cognitive Science Research paper No 176
    Emotions involve complex processes produced by interactions between motives, beliefs, percepts, etc. E.g. real or imagined fulfilment or violation of a motive, or triggering of a 'motive-generator', can disturb processes produced by other motives. To understand emotions, therefore, we need to understand motives and the types of processes they can produce. This leads to a study of the global architecture of a mind. Some constraints on the evolution of minds are discussed. Types of motives and the processes they generate are sketched.

    (Note we now use slightly different terminology from that used in this paper. In particular, what the paper labelled as "intensity" we now call "insistence", i.e. the capacity to divert attention from other things.)

    This paper is often misquoted as arguing that robots (or at least intelligent robots) should have emotions. On the contrary, the paper argues that certain sorts of high level disturbances (i.e. emotional states) will be capable of arising out of interactions between mechanisms that exist for other reasons. Similarly 'thrashing' is capable of occurring in multi-processing operating systems that support swapping and paging, but that does not mean that operating systems should produce thrashing.

    A more recent analysis of the confused but fashionable arguments (e.g. based on Damasio's writings) claiming that emotions are needed for intelligence can be found in this semi-popular presentation.

    One of the arguments is analogous to arguing that a car requires a functioning horn for its starter motor to work, because damaging the battery can disable the horn and disable the starter motor.

  83. Filename: sloman-clowestribute.html
    Filename: sloman-clowestribute.pdf

    Title: Experiencing Computation: A tribute to Max Clowes
    (Originally appeared in Computing in Schools 1981)
    Author: Aaron Sloman

    Date installed:
    11 Feb 2001 (Originally published 1981)


    Max Clowes (pronounced as if spelt Clues, or Klews) was one of the pioneers of AI vision research in the UK. He inspired and helped to develop Artificial Intelligence and computational Cognitive Science at he University of Sussex. In 1981 he tragically died, shortly after leaving the University in order to work on computing in Schools. This paper was originally published in 1981. The version here has had some footnotes added referring to subsequent developments.

  84. Filename: sloman-deep-and-shallow-1981.html (HTML)
    Filename: sloman-deep-and-shallow-1981.pdf (PDF)

    Title: Deep and shallow simulations
    Commentary on: Modeling a paranoid mind, by Kenneth Mark Colby
    The Behavioral and Brain Sciences (1981) 4(04) pp 515-534


    A deep simulation attempts to model mental processes, whereas a shallow simulation attempts only to replicate behaviour. The question raised by Colby's paper is, What can we learn from a shallow simulation?


  85. Filename: sloman-ullman-gibson-bbs.pdf (PDF)
    Title: What kind of indirect process is visual perception?

    Author: Aaron Sloman
    Date: Originally published 1980. Added here 28 Sep 2012

    Where published:

    In: Open Peer Commentary on Shimon Ullman: `Against Direct Perception'
    Behavioral and Brain Sciences Journal, (BBS) (1980) 3, pp. 401-404

    The whole publication, including commentaries is:

    S. Ullman, Against direct perception
    The Behavioral And Brain Sciences (1980) 3, 373-415
    No abstract in paper. Will add a summary here later.

    Compare my more recent discussion of Gibson:
    Aaron Sloman, What's vision for, and how does it work? From Marr (and earlier) to Gibson and Beyond,
    Online tutorial presentation, Sep, 2011. Also at

  86. Filename:sloman-croucher-searle.pdf
    Title: How to turn an information processor into an understander
    Commentary on John R. Searle: Minds, brains, and programs

    Authors:Aaron Sloman and Monica Croucher
    Date: Originally published 1980, installed here 9 Oct 2012

    Where published:

    Commentary on 'Minds, brains, and programs' by John R. Searle
    in The Behavioral and Brain Sciences Journal (BBS) (1980) 3, 417-457
    This commentary: pages 447-448
    Searle's delightfully clear and provocative essay contains a subtle mistake, which is also often made by Al researchers who use familiar mentalistic language to describe their programs. The mistake is a failure to distinguish form from function.

    That some mechanism or process has properties that would, in a suitable context, enable it to perform some function, does not imply that it already performs that function. For a process to be understanding, or thinking, or whatever, it is not enough that it replicate some of the structure of the processes of understanding, thinking, and so on. It must also fulfil the functions of those processes. This requires it to be causally linked to a larger system in which other states and processes exist. Searle is therefore right to stress causal powers. However, it is not the causal powers of brain cells that we need to consider, but the causal powers of computational processes. The reason the processes he describes do not amount to understanding is not that they are not produced by things with the right causal powers, but that they do not have the right causal powers, since they are not integrated with the right sort of total system.


  87. Filename: sloman.primacy.inner.language.pdf
    Filename: sloman.primacy.inner.language.txt (Plain text)

    Title: The primacy of non-communicative language

    Author: Aaron Sloman

    In The Analysis of Meaning, Proceedings 5,
    (Invited talk for ASLIB Informatics Conference, Oxford, March 1979,)
    ASLIB and British Computer Society, London, 1979.
    Eds M. MacCafferty and K. Gray, pages 1--15.
    Date: Originally published 1979. Added here 2 Dec 2000


    How is it possible for symbols to be used to refer to or describe things? I shall approach this question indirectly by criticising a collection of widely held views of which the central one is that meaning is essentially concerned with communication. A consequence of this view is that anything which could be reasonably described as a language is essentially concerned with communication. I shall try to show that widely known facts, for instance facts about the behaviour of animals, and facts about human language learning and use, suggest that this belief, and closely related assumptions (see A1 to A3, in the paper) are false. Support for an alternative framework of assumptions is beginning to emerge from work in Artificial Intelligence, work concerned not only with language but also with perception, learning, problem-solving and other mental processes. The subject has not yet matured sufficiently for the new paradigm to be clearly articulated. The aim of this paper is to help to formulate a new framework of assumptions, synthesising ideas from Artificial Intelligence and Philosophy of Science and Mathematics.

  88. Filename: sloman-epist-ai.pdf
    Title: Epistemology and Artificial Intelligence

    Authors: Aaron Sloman
    Date Installed: 29 Aug 2009; Moved here 17 Apr 2019

    Where published:

    In Donald Michie (Editor) Expert Systems in the Microelectronic Age (Edinburgh University Press, 1979)


    A brief introduction to the main problems of epistemology as understood by philosophers and an explanation of (a) why they are relevant to AI, and (b) how they are transformed in the context of AI as the science of natural and artificial intelligent systems.


  89. 1978 Book:

    Philosophy science and models of mind.

    Author: Aaron Sloman
                 (University of Sussex. At the University of Birmingham since 1991.)

    Date installed: 29 Sep 2001
    Last updated: 19 Aug 2016

    Abstract: See the book contents list

    Published 1978: Revised Version, August 2016


    The book was originally published by Harvester Press and Humanities Press in 1978, but has been out of print for many years. It is now available online free of charge, with additional notes and some re-drawn images, under a Creative Commons licence.

    The original was photocopied by Manuela Viezzer in 2000, then scanned in by Sammy Snow. A lot of work remained to be done, correcting OCR errors and re-drawing the diagrams (for which I used the 'tgif' package on Linux). Since then most chapters have had additional notes and comments added, all clearly marked as new additions. In July 2015 the separate parts (except for the index) were combined to one integrated document with internal cross-references and made available in html and pdf formats listed above.

    Some reviews of the 1978 version are listed below and in the online edition of the book.


    • After the book had been scanned, a collection of separate chapters was made available at this web site (originally HTML only, then PDF versions were added). Those have now been merged into the new integrated version above.

    • Note added 10 Aug 2015
      I have discovered that a 2012 version of this book has been made available on the Archive.Org web site ( a non-profit organisation building an internet library. The book is available there in various formats:
      I don't know whether that archived version will ever be updated.

    • There is an out of date version online at the eprints web site(PDF) of ASSC
      (Association for the Scientific Study of Consciousness).

    • Kindle Ebook Version: added 18 Dec 2011
      Sergei Kaunov converted the online version available in 2011 to Amazon kindle format. (Alas now out of date.) It is available for download at a very low cost (the minimum allowed by Amazon): from

      Product description added by Sergei Kaunov:

      "It is a 1978 book on Artificial Intelligence by Aaron Sloman, professor of Birmingham University. It's not just interesting or representative, it is remarkable for the fact that through the years passed, from the time the book was written, it found its realization in real life like a step-by-step plan. The book mainly consists of philosophical and engineering ideas on intelligence (not only artificial) and relevant topics. After the decades passed we can compare prognoses and current state of the art which shows how these ideas meet its implementation today. Such confirmations highly raise the value of other, more abstract, and further conclusions we can get from the book. One of the core ideas of the book is the described approach which was applied and developed by author at the Birmingham university for AI construction and study of intellect, and the once started work is still on. So insights provided by this book show the beginning of coherent and complex actual research on human and artificial intelligence.
      It is a rare kind of scientific or philosophical book which become more valuable with time."

    • Kindle Mobi-file:
      Created by Sergei Kaunov
    • Epub-file:
      Created by Sergei Kaunov

    Reviews by Douglas Hofstadter and Steven Stich

    Added 4 Oct 2007: Hofstadter Review
    I have discovered that a review of 'The Computer Revolution in Philosophy'
    by Douglas Hofstadter is available online:
    Volume 2, Number 2, March 1980 (Copyright 1980 American Mathematical Society)
    The computer revolution in philosophy: Philosophy, science and models of mind
    by Aaron Sloman, Harvester Studies in Cognitive Science Humanities Press,
    Atlantic Highlands, N. J., 1978, xvi + 304 pp., cloth, $22.50.
    Reviewed by Douglas R. Hofstadter

    (The review rightly criticises some of the unnecessarily aggressive tone and
    throw-away remarks, but also gives the most thorough assessment of the main
    ideas of the book that I have seen.
    Like many reviewers and AI researchers, Hofstadter, like Stich (see below) regards the philosophy
    of science in the first part of the book, e.g. Chapter 2, as relatively uninteresting, whereas I think
    understanding those issues is central to understanding how human minds work as they learn
    about the world and about themselves, and also central to any good philosophy of science.)

    Added 23 Jul 2015: Stich Review
    A review of this book was published by Steven P. Stich, in 1981

    The Computer Revolution in Philosophy: Philosophy, Science and Models of Mind,
    by Aaron Sloman. Reviewed by Stephen P. Stich in
    The Philosophical Review,
    Vol. 90, No. 2 (Apr., 1981), pp. 300-307

    That review has now been made available, with the author's permission, here:

    The review (like Hofstadter's review) criticised the notion of 'Explaining possibilities' as one
    of the aims of science and my use of Artificial Intelligence as an example, in Chapter 2.

    Response to reviews
    A partial response to the reviews by Stich and Hofstadter is available here:
    Construction kits as explanations of possibilities (generators of possibilities)
    (Work in progress.)

  90. Filename: bbs-chimps-1978.pdf
    Filename: bbs-chimps-1978.html
    Title: What About Their Internal Languages?

    Author: Aaron Sloman
    Date Installed: 13 Dec 2007 (Originally published 1978)


    Commentary on three articles published in Behavioral and Brain Sciences Journal 1978, 1 (4)
    1. Premack, D., Woodruff, G. Does the chimpanzee have a theory of mind? BBS 1978 1 (4): 515.
    2. Griffin, D.R. Prospects for a cognitive ethology. BBS 1978 1 (4): 527.
    3. Savage-Rumbaugh, E.S., Rumbaugh, D.R., Boysen, S. Linguistically-mediated tool use and exchange by chimpanzees (Pan Troglodytes). BBS 1978 1 (4): 539.
    Despite the virtues of the target articles, I find something sadly lacking: an awareness of deep problems and a search for deep explanations.

    Are the authors of these papers merely concerned to collect facts? Clearly not: they are also deeply concerned to learn the extent of man's uniqueness in the animal world, to refute behaviourism, and to replace anecdote with experimental rigour. But what do they have to say to someone who doesn't care whether humans are unique, who believes that behaviourism is either an irrefutable collection of tautologies or a dead horse, and who already is deeply impressed by the abilities of cats, dogs, chimps, and other animals, but who constantly wonders: HOW DO THEY DO IT?

    My answer is that the papers do not have much to say about that: for that, investigation of designs for working systems is required, rather than endless collection of empirical facts, interesting as those may be.

    See also The primacy of non-communicative language (Above)

  91. Filename:sloman-et-al-78.pdf
    Title: Representation and Control in Vision

    Authors: Aaron Sloman, David Owen, Geoffrey Hinton, Frank O'Gorman
    Date Installed: 10 Jun 2012 (Published 1978)

    Where published:

    in Proceedings AISB/GI Conference, 18-20th July 1978,
    Hamburg, Germany
    Programme Chair: Derek Sleeman
    Program Committee:
        Alan Bundy (Edinburgh)
        Steve Hardy (Sussex)
        H. -H. Nagel (Hamburg)
        Jacques Pitrat (Paris)
        Derek Sleeman (Leeds)
        Yorick Wilks (Essex)
    General chair: K. -H. NAGEL

    Published by: SSAISB and GI


    (Extract from text)
    Vision work in AI has made progress with relatively small problems. We are not aware of any system in which many different kinds of knowledge co-operate. Often there is essentially one kind of structure, e.g. a network of lines or regions, and the problem is simply to segment it, and/or to label parts of it. Sometimes models of known objects are used to guide the analysis and interpretation of an image, as in the work of Roberts (1965), but usually there are few such models, and there isn't a very deep hierarchy of objects composed of objects composed of objects....
    By contrast, recent speech understanding systems, like HEARSAY (Lesser 1977, Hayes-Roth 1977), deal with more complex kinds of interactions between different sorts of knowledge. They are still not very impressive compared with people, but there are some solid achievements. Is the lack of similar success in vision due to inherently more difficult problems?
    Some vision work has explored interactions between different kinds of knowledge, including the Essex coding-sheet project (Brady, Bornat 1976) based on the assumption that provision for multiple co-existing processes would make the tasks much easier. However, more concrete and specific ideas are required for sensible control of a complex system, and a great deal of domain-specific descriptive know-how has to be explicitly provided for many different sub-domains.

    The POPEYE project is an attempt to study ways of putting different kinds of visual knowledge together in one system.

    Chapter 9 of The Computer Revolution in Philosophy provides further information about the Popeye system.

  92. Filename: sloman-on-pylyshyn-bbs-1978.html
    Filename: sloman-on-pylyshyn-bbs-1978.pdf
    Title: Artificial Intelligence and Empirical Psychology

    Author: Aaron Sloman
    Date Installed: 9 Oct 2012 (Originally published 1978) (Html 8 Feb 2016)
    Commentary on Z. Pylyshyn:
    Computational models and empirical constraints
    Behavioral and Brain Sciences Vol 1 Issue 1 March 1978, pp 91 - 99

    This commentary: pp 115-6



  93. Filename: aims-of-science-Sloman.html (HTML)
    Filename: aims-of-science-Sloman.pdf (PDF)
    Author: Aaron Sloman (1976)
    Installed: 28 Jul 2014
    Title: What are the aims of science?
    Originally published
    Radical Philosophy, Issue 13, pages 7-17, 1976

    Installed here: 28 Jul 2014

    If we are to understand the nature of science, we must see it as an
    activity and achievement of the human mind alongside others, such as the
    achievements of children in learning to talk and to cope with people and other
    objects in their environment, and the achievements of non-scientists living in a
    rich and complex world which constantly poses problems to be solved. Looking at
    scientific knowledge as one form of human knowledge, scientific understanding as
    one form of human understanding, scientific investigation as one form of human
    problem-solving activity, we can begin to see more clearly what science is, and
    also what kind of mechanism the human mind is.

    By undermining the slogan that science is the search for laws, and subsidiary
    slogans such as that quantification is essential, that scientific theories must
    be empirically refutable, and that the methods of philosophers cannot serve the
    aims of scientists, I shall try, in what follows, to liberate some scientists
    from the dogmas indoctrinated in universities and colleges. I shall also try to
    show philosophers how they can contribute to the scientific study of man,
    thereby escaping from the barrenness and triviality complained of so often by
    non-philosophers and philosophy students.

    A side-effect which will be reported elsewhere, is to undermine some old
    philosophical distinctions and pour cold water on battles which rage around them
    -- like the distinction between subjectivity and objectivity, and the battles
    between empiricists and rationalists.

    Key idea: A major aim of science is not to discover and explain laws, but to
    discover what is possible, and how it is possible.

    This view of science developed further in Sloman (1978) helps to explain the
    contributions of Theoretical Linguistics, Chemistry, Artificial Intelligence,
    and Computer Science insofar as they all enrich our understanding of what is
    possible and how it is possible.


  94. Filename: sloman-afterthoughts.pdf
    (Via LaTeX: derived from a scanned version)
    Filename: sloman-tinlap-1975.pdf (original formatting: also here)
    Title: Afterthoughts on Analogical Representations (1975)
    Originally Published in in Theoretical Issues in Natural Language Processing (TINLAP-1), Eds. R. Schank & B. Nash-Webber, pp. 431--439, MIT,
    Now available online
    Reprinted in Readings in knowledge representation, Eds. R.J. Brachman & H.J. Levesque, Morgan Kaufmann, 1985.
    Author: Aaron Sloman
    Date installed: 28 Mar 2005


    In 1971 I wrote a paper attempting to relate some old philosophical issues about representation and reasoning to problems in Artificial Intelligence. A major theme of the paper was the importance of distinguishing "analogical" from "Fregean" representations. I still think the distinction is important, though perhaps not as important for current problems in A.I. as I used to think. In this paper I'll try to explain why.


  95. Filename: sloman-bogey.html (HTML)
    Filename: sloman-bogey.pdf (incomplete PDF from OCR)
    Filename: sloman-bogey-print.pdf

    (A more complete, PDF version, derived from the html version.)

    Title: Physicalism and the Bogey of Determinism

    Author: Aaron Sloman
    Date: Published 1974, installed here 29 Dec 2005


    Presented at an interdisciplinary conference on Philosophy of Psychology at the University of Kent in 1971. Published in the proceedings, as
    A. Sloman, 'Physicalism and the Bogey of Determinism'
    (along with Reply by G. Mandler and W. Kessen, and additional comments by Alan R. White, Philippa Foot and others, and replies to criticisms)
    in Philosophy of Psychology, Ed S.C.Brown, London: Macmillan, 1974, pages 293--304. (Published by Barnes & Noble in USA.)
    Commentary and discussion followed on pages 305--348.
    This paper rehearses some relatively old arguments about how any coherent notion of free will is not only compatible with but depends on determinism.
    However the mind-brain identity theory is attacked on the grounds that what makes a physical event an intended action A is that the agent interprets the physical phenomena as doing A. The paper should have referred to the monograph Intention (1957) by Elizabeth Anscombe (summarised here by Jeff Speaks), which discusses in detail the fact that the same physical event can have multiple (true) descriptions, using different ontologies.
    My point is partly analogous to Dennett's appeal to the 'intentional stance', though that involves an external observer attributing rationality along with beliefs and desires to the agent. I am adopting the design stance not the intentional stance, for I do not assume rationality in agents with semantic competence (e.g. insects), and I attempt to explain how an agent has to be designed in order to perform intentional actions; the design must allow the agent to interpret physical events (including events in its brain) in a way that is not just perceiving their physical properties. That presupposes semantic competence which is to be explained in terms of how the machine or organism works, i.e. using the design stance, not by simply postulating rationality and assuming beliefs and desires on the basis of external evidence.

    Some of ideas that were in the paper and in my responses to commentators were also presented in The Computer Revolution in Philosophy, including a version of this diagram (originally pages 344-345, in the discussion section below), discussed in more detail in Chapter 6 of the book, and later elaborated as an architectural theory assuming concurrent reactive, deliberative and metamanagement processes, e.g. as explained in this 1999 paper Architecture-Based Conceptions of Mind, and later papers.
    The html paper preserves original page divisions.
    (I may later add further notes and comments to this HTML version.)

    Note added 3 May 2006
    An online review of the whole book is available here. by Marius Schneider, O. F. M., The Catholic University of America, Washington, D. C., apparently written in 1975.

  96. Filename: sloman-aisb-1974.pdf (Scanned from original: about 1.8MB)
    Title: On learning about numbers: Some problems and speculations
    In Proceedings AISB Conference 1974, University of Sussex, pp. 173--185,

    A slightly revised version (with clearer diagrams) was published as Chapter 8 of the 1978 book: The Computer Revolution in Philosophy

    Author: Aaron Sloman

    Date: Published/Presented 1974, installed here 3 Jan 2010.


    The aim of this paper is methodological and tutorial. It uses elementary number competence to show how reflection on the fine structure of familiar human abilities generates requirements exposing the inadequacy of initially plausible explanations. We have to learn how to organise our common sense knowledge and make it explicit, and we don't need experimental data as much as we need to extend our model-building know-how.




  97. Filename: sloman-new-bodies.pdf (PDF)
    Filename: sloman-new-bodies.html (HTML)
    Title: New Bodies for Sick Persons: Personal Identity Without Physical Continuity

    Author: Aaron Sloman
    First published in In Analysis vol 32 NO 2, December 1971, pages 52 --55
    Date Installed: 9 Jan 2007 (Originally Published 1971)

    Abstract: (Extracts from paper)

    In his recent Aristotelian society paper ('Personal identity, personal relationships, and criteria' in Proceedings the Aristotelian Society, 1970-71, pp. 165--186), J. M. Shorter argues that the connexion between physical identity and personal identity is much less tight than some philosophers have supposed, and, in order to drive a wedge between the two sorts of identity, he discusses logically possible situations in which there would be strong moral and practical reasons for treating physically discontinuous individuals as the same person. I am sure his main points are correct: the concept of a person serves a certain sort of purpose and in changed circumstances it might be able to serve that purpose only if very different, or partially different, criteria for identity were employed. Moreover, in really bizarre, but "logically" possible, situations there may be no way of altering the identity-criteria, nor any other feature of the concept of person, so as to enable the concept to have the same moral, legal, political and other functions as before: the concept may simply disintegrate, so that the question 'Is X really the same person as Y or not ?', has no answer at all. For instance, this might be the case if bodily discontinuities and reduplications occurred very frequently. To suppose that the "essence" of the concept of a person, or some set of general logical principles, ensures that questions of identity always have answers in all possible circumstances, is quite unjustified.

    In order to close a loophole in Shorter's argument I describe a possible situation in which both physical continuity and bodily identity are clearly separated from personal identity. Moreover, the example does not, as Shorter's apparently does, assume the falsity of current physical theory.

    It will be a long time before engineers make a machine which will not merely copy a tape recording of a symphony, but also correct poor intonation, wrong notes, or unmusical phrasing. An entirely new dimension of understanding of what is being copied is required for this. Similarly, it may take a further thousand years, or more, before the transcriptor is modified so that when a human body is copied the cancerous or other diseased cells are left out and replaced with normal healthy cells, if, by then, the survival rate for bodies made by this modified machine were much greater than for bodies from which tumours had been removed surgically, or treated with drugs, then I should have little hesitation, after being diagnosed as having incurable cancer, in agreeing to have my old body replaced by a new healthy one, and the old one destroyed before recovering from the anaesthetic. This would be no suicide, nor murder.

  98. Filename: sloman-ijcai-71.pdf (PDF Scanned from IJCAI Proceedings)
    (with full list of references -- added June 2006)

  99. Filename: sloman-analogical-1971 (HTML)
  100. Filename: sloman-analogical-1971.pdf (PDF derived from HTML)
  101. Filename: sloman-71-AIJ.pdf (PDF: version in AI Journal)

    Title: Interactions between Philosophy and Artificial Intelligence: The role of intuition and non-logical reasoning in intelligence,
    Author: Aaron Sloman

    Originally published in:

    Proceedings IJCAI 1971
    (Proceedings also available here)
    , then reprinted in
    Artificial Intelligence, vol 2, 1971,
    then in
    J.M. Nicholas, ed. Images, Perception, and Knowledge, Dordrecht-Holland: Reidel. 1977

    This was later revised as Chapter 7 of The Computer Revolution in Philosophy (1978)

    Date added: 12 May 2004


    This paper echoes, from a philosophical standpoint, the claim of McCarthy and Hayes that Philosophy and Artificial Intelligence have important relations. Philosophical problems about the use of 'intuition' in reasoning are related, via a concept of analogical representation, to problems in the simulation of perception, problem-solving and the generation of useful sets of possibilities in considering how to act. The requirements for intelligent decision-making proposed by McCarthy and Hayes in Some Philosophical Problems from the Standpoint of Artificial Intelligence (1969) are criticised as too narrow, because they allowed for the use of only one formalism, namely logic. Instead general requirements are suggested showing the usefulness of other forms of representation.

    There were several sequels to this paper including the Afterthoughts paper written in 1975, some further developments regarding ontologies and criteria for adequacy in a 1984-5 paper and several other papers mentioned in the section on diagrammatic/visual reasoning here.

    Response by Pat Hayes
    A much cited paper by Hayes discussing issues raised in the 1971 paper and elsewhere
    was presented at the AISB Conference at Sussex University in 1974, and later
    reprinted in the collection mentioned below. In view of its general significance and
    unavailability online I have included the 1974 Conference version here, with the
    permission of the author.

    File: hayes-aisb-1974-prob-rep.pdf (PDF)
    Patrick J. Hayes "Some Problems and Non-Problems in Representation Theory"
    in Proceedings AISB Summer Conference, 1974
    University of Sussex

    Reprinted in: Readings in knowledge representation,
    Eds. R.J. Brachman and H.J. Levesque, Morgan Kaufmann, Los Altos, California, 1985

    Related work includes these presentations:

  102. Filename: sloman-tarski-liar.pdf (PDF)
  103. Filename: sloman-tarski-liar.html (HTML)

    Title: Tarski, Frege and the Liar Paradox

    Originally in Philosophy, Vol XLVI, pages 133-147, 1971
    Author: Aaron Sloman
    Date installed: 16 Oct 2003


    The paper attempts to resolve a variety of logical and semantic paradoxes on the basis of Frege's ideas about compositional semantics: i.e. complex expressions have a reference that depends on the references of the component parts and the mode of composition, which determines a function from the lowest level components to the value for the whole expression. The paper attempts to show that it is inevitable within this framework that some syntactically well formed expressions will fail to have any reference, even though they may have a well defined sense. This can be compared with the ways in which syntactically well-formed programs in programming languages may fail to terminate or in some other way fail semantically and produce run-time errors.

    The paper suggests that this view of paradoxes, including the paradox of the Liar, is superior to Tarski's analysis which required postulating a hierarchy of meta-languages. We do not need such a hierarchy to explain what is going on or to deal with the fact that such paradoxes exist. Moreover, the hierarchy would not necessarily be useful for an intelligent agent, compared with languages that contain their own meta-language, like the one I am now using.


  104. Filename: sloman-ought-and-better.html
  105. Filename: ought-better.pdf
  106. Filename: (scanned version)
    Title: 'Ought' and 'Better'

    Author: Aaron Sloman
    Date Installed: 19 Sep 2005


    Originally published as Aaron Sloman, 'Ought and Better' Mind, vol LXXIX, No 315, July 1970, pp 385--394)

    This is a sequel to the 1969 paper on "How to derive 'Better' from 'Is'" also online at this web site. It presupposes the analysis of 'better' in the earlier paper, and argues that statements using the word 'ought' say something about which of a collection of alternatives is better than the others, in contrast with statements using 'must' or referring to 'obligations', or what is 'obligatory'. The underlying commonality between superficially different statements like 'You should take an umbrella with you' and 'The sun should come out soon' is explained, along with some other philosophical puzzles, e.g. concerning why 'ought' does not imply 'can', contrary to what some philosophers have claimed.

    Curiously, the 'Ought' and 'Better' paper is mentioned at in the section on David Lodge's novel "Thinks...", which includes a reference to this paper 'What to Do If You Want to Go to Harlem: Anankastic Conditionals and Related Matters' by Kai von Fintel and Sabine Iatridou (MIT), which includes a discussion of the paper on 'Ought' and 'Better'.


  107. Filename: sloman-transformations.pdf
    Title: Transformations of Illocutionary Acts (1969)

    Author: Aaron Sloman
    First published in Analysis Vol 30 No 2, December 1969 pages 56-59
    Date Installed: 10 Jan 2007

    Abstract: (extracts from paper)

    This paper discusses varieties of negation and other logical operators when applied to speech acts, in response to an argument by John Searle.

    In his book Speech Acts (Cambridge University Press, 1969), Searle discusses what he calls 'the speech act fallacy' (pp. 136,ff), namely the fallacy of inferring from the fact that

    (1) in simple indicative sentences, the word W is used to perform some speech-act A (e.g. 'good' is used to commend, 'true' is used to endorse or concede, etc.)
    the conclusion that
    (2) a complete philosophical explication of the concept W is given when we say 'W is used to perform A'.
    He argues that as far as the words 'good', 'true', 'know' and 'probably' are concerned, the conclusion is false because the speech-act analysis fails to explain how the words can occur with the same meaning in various grammatically different contexts, such as interrogatives ('Is it good?'), conditionals('If it is good it will last long'), imperatives ('Make it good'), negations, disjunctions, etc.

    The paper argues that even if conclusion (2) is false, Searle's argument against it is inadequate because he does not consider all the possible ways in which a speech-act might account for non-indicative occurrences.

    In particular, there are other things we can do with speech acts besides performing them and predicating their performance, e.g. besides promising and expressing the proposition that one is promising. E.g. you can indicate that you are considering performing act F but are not yet prepared to perform it, as in 'I don't promise to come'. So the analysis proposed can be summarised thus:

    If F and G are speech acts, and p and q propositional contents or other suitable objects, then:

    o Utterances of the structure 'If F(p) then G(q)' express provisional commitment to performing G on q, pending the performance of F on p
    o Utterances of the form 'F(p) or G(q) 'would express a commitment to performing (eventually) one or other or both of the two acts though neither is performed as yet.
    o The question mark, in utterances of the form 'F(p)?' instead of expressing some new and completely unrelated kind of speech act, would merely express indecision concerning whether to perform F on p together with an attempt to get advice or help in resolving the indecision.
    o The imperative form 'Bring it about that . .' followed by a suitable grammatical transformation of F(p) would express the act of trying to get (not cause) the hearer to bring about that particular state of affairs in which the speaker would perform the act F on p (which is not the same as simply bringing it about that the speaker performs the act).
    It is not claimed that 'not', 'if', etc., always are actually used in accordance with the above analyses, merely that this is a possible type of analysis which (a) allows a word which in simple indicative sentences expresses a speech act to contribute in a uniform way to the meanings of other types of sentences and (b) allows signs like 'not', 'if', the question construction, and the imperative construction, to have uniform effects on signs for speech acts. This type of analysis differs from the two considered and rejected by Searle. Further, if one puts either assertion or commendation or endorsement in place of the speech acts F and G in the above schemata, then the results seem to correspond moderately well with some (though not all) actual uses of the words and constructions in question. With other speech acts, the result does not seem to correspond to anything in ordinary usage: for instance, there is nothing in ordinary English which corresponds to applying the imperative construction to the speech act of questioning, or even commanding, even though if this were done in accordance with the above schematic rules the result would in theory be intelligible.

  108. Filename:
  109. Filename:
    Title: How to derive "better" from "is",

    Author: Aaron Sloman
    Originally Published as: A. Sloman How to derive "better" from "is" American Philosophical Quarterly,
    Vol 6, Number 1, Jan 1969, pp 43--52.
    Date Installed here: 23 Oct 2002


    ONE type of naturalistic analysis of words like "good," "ought," and "better" defines them in terms of criteria for applicability which vary from one context to another (as in "good men," "good typewriter," "good method of proof"), so that their meanings vary with context. Dissatisfaction with this "crude" naturalism leads some philosophers to suggest that the words have a context-independent non-descriptive meaning defined in terms of such things as expressing emotions, commanding, persuading, or guiding actions.

    There are well-known objections to both approaches, and the aim of this paper is to suggest an alternative which has apparently never previously been considered, for the very good reason that at first sight it looks so unpromising, namely the alternative of defining the problematic words as logical constants.

    This should not be confused with the programme of treating them as undefined symbols in a formal system, which is not new. In this essay an attempt will be made to define a logical constant "Better" which has surprisingly many of the features of the ordinary word "better" in a large number of contexts. It can then be shown that other important uses of "better" may be thought of as derived from this use of the word as a logical constant.

    The new symbol is a logical constant in that its definition (i.e., the specification of formation rules and truth-conditions for statements using it) makes use only of such concepts as "entailment," "satisfying a condition," "relation," "set of properties," which would generally be regarded as purely logical concepts. In particular, the definition makes no reference to wants, desires, purposes, interests, prescriptions, choice, non-descriptive uses of language, and the other paraphernalia of non-naturalistic (and some naturalistic) analyses of evaluative words.

    (However, some of those 'paraphernalia' can be included in arguments/subjects to which the complex relational predicate 'better' is applied.)

    NOTE Added 7 Nov 2013
    I was under the impression that no philosophers had ever paid any attention to this
    paper. I've just discovered a counter example:
        Paul Bloomfield 'Prescriptions Are Assertions: An Essay On Moral Syntax'
        American Philosophical Quarterly Vol 35, No 1, January 1998


  110. Filename: sloman-explain-necessity.pdf
    (132 KBytes, via latex from OCR -- PDF)

    Filename: sloman-ExplainNecessity.pdf
    (11.4 MB Scanned PDF from original)

    Title: Explaining Logical Necessity

    Author: Aaron Sloman
    Date Installed: 4 Dec 2007 (Published originally in 1968); Updated 19 Dec 2009
    in Proceedings of the Aristotelian Society, 1968/9, Volume, 69, pp 33--50.
    Abstract: (From the introductory section)
    I: Some facts about logical necessity stated.
    II: Not all necessity is logical.
    III: The need for an explanation.
    IV: Formalists attempt unsuccessfully to reduce logic to syntax.
    V: The no-sense theory of Wittgenstein's Tractatus merely reformulates
    the problem.
    VI: Crude conventionalism is circular.
    VII: Extreme conventionalism is more sophisticated.
    VIII: It yields some important insights.
    IX: But it ignores the variety of kinds of proof.
    X: Proofs show why things must be so, but different proofs show different things. Hence there can be no general explanation of necessity.

    I An adequate theory of meaning and truth must account for the following facts, whose explanation is the topic, though not the aim, of the paper.

    (i) Different signs (e.g., in different languages) may express the same proposition.

    (ii) The syntactic and semantic rules in virtue of which sentences are able to express contingent propositions also permit the expression of necessary propositions and generate necessary relations between contingent propositions. E.g. although 'It snows in Sydney or it does not snow in Sydney' can be verified empirically (since showing one disjunct to be true would be an empirical verification, just as a proposition of the form 'p and not-p' can be falsified empirically), the empirical enquiry can be short-circuited by showing what the result must be.

    (iii) At least some such restrictions on truth-values, or combinations of truth-values (e.g., when two or more contingent propositions are logically equivalent, or inconsistent, or when one follows from others), result from purely formal, or logical, or topic-neutral features of the construction of the relevant propositions, features which have nothing to do with precisely which concepts occur, or which objects are referred to. Hence we call some propositions logically true, or logically false, and say some inferences are valid in virtue of their logical form, which prevents simultaneous truth of premisses and falsity of conclusion.

    (iv) The truth-value-restricting logical forms are systematically inter-related so that the whole infinite class of such forms can be recursively generated from a relatively small subset, as illustrated in axiomatisations of logic.

    Subsequent discussion will show these statements to be over-simple. Nevertheless, they will serve to draw attention to the range of facts whose need of explanation is the starting point of this paper. They have deliberately been formulated to allow that there may be cases of non-logical necessity.




  111. Title: Functions and Rogators (1965)
    Author: Aaron Sloman

    Available in three formats:

    Date Installed: 23 Dec 2007; Updated 5 Apr 2016

    This paper was originally presented at a meeting of the Association for Symbolic Logic held in St. Anne's College, Oxford, England from 15-19 July 1963 as a NATO Advanced Study Institute with a Symposium on Recursive Functions sponsored by the Division of Logic, Methodology and Philosophy of Science of the International Union of the History and Philosophy of Science.

    A summary of the meeting by E. J. Lemmon, M. A. E. Dummett, and J. N. Crossley with abstracts of papers presented, including this one, was published in The Journal of Symbolic Logic, Vol. 28, No. 3. (Sep., 1963), pp. 262-272. accessible online here.

    The full paper was published in the conference proceedings:
    Aaron Sloman 'Functions and Rogators', in
    Formal Systems and Recursive Functions:
    Proceedings of the Eighth Logic Colloquium Oxford, July 1963
    Eds J N Crossley and M A E Dummett
    North-Holland Publishing Co (1965), pp. 156--175

    This paper extends Frege's concept of a function to "rogators", which are like functions in that they take arguments and produce results, but are unlike functions in that their results can depend on the state of the world, in addition to which arguments they are applied to.

    It was scanned in and digitised in December 2007. The html version was re-formatted on 5 Apr 2016 and a corresponding "lightweight" PDF version derived from it. The original 15MB scanned PDF file is now sloman-rogators-orig.pdf

    The key ideas were originally presented in the author's Oxford DPhil Thesis (Aaron Sloman, 1962): Knowing and Understanding
    (Now online).

    This paper was described by David Wiggins as 'neglected but valuable' in his 'Sameness and Substance Renewed' (2001).

    (Published also in E. J. Lemmon, M. A. E. Dummett, and J. N. Crossley) (1963)
    Frege, and others, have made extensive use of the notion of a function, for example in analysing the role of quantification, the notion of a function being defined, usually, in the manner familiar to mathematicians, and illustrated with mathematical examples. On this view functions satisfy extensional criteria for identity. It is not usually noticed that in non-mathematical contexts the things which are thought of as analogous to functions are, in certain respects, unlike the functions of mathematics. These differences provide a reason for saying that there are entities, analogous to functions, but which do not satisfy extensional criteria for identity. For example, if we take the supposed function 'x is red' and consider its value (truth or falsity) for some such argument as the lamp post nearest my front door, then we see that what the value is depends not only on which object is taken as argument, and the 'function', but also on contingent facts about the object, in particular, what colour it happens to have. Even if the lamp post is red (and the value is truth), the same lamp post might have been green, if it had been painted differently. So it looks as if we need something like a function, but not extensional, of which we can say that it might have had a value different from that which it does have. We cannot say this of a function considered simply as a set of ordered pairs, for if the same argument had had a different value it would not have been the same function. These non-extensional entities are described as 'rogators', and the paper is concerned to explain what the function-rogator distinction is, how it differs from certain other distinctions, and to illustrate its importance in logic, from the philosophical point of view.

  112. Filename: sloman-necessary.pdf (PDF)
    Filename: sloman-necessary.html (HTML)

    Author: Aaron Sloman

    Date Installed: 9 Jan 2007 (Published 1965)

    First published in Analysis vol 26, No 1, pp 12-16 1965.
    Abstract (actually the opening paragraph of the paper):
    It is frequently taken for granted, both by people discussing logical distinctions and by people using them, that the terms 'necessary', 'a priori', and 'analytic' are equivalent, that they mark not three distinctions, but one. Occasionally an attempt is made to establish that two or more of these terms are equivalent. However, it seems me far from obvious that they are or can be shown to be equivalent, that they cannot be given definitions which enable them to mark important and different distinctions. Whether these different distinctions happen to coincide or not is, as I shall show, a further question, requiring detailed investigation. In this paper, an attempt will be made to show in a brief and schematic way that there is an open problem here and that it is extremely misleading to talk as if there were only one distinction.


  113. Filename: rules-premisses.html (HTML)
    Filename: rules-premisses.pdf (PDF)
    Title: Rules of inference, or suppressed premisses? (1964)

    Author: Aaron Sloman
    Date Installed: 31 Dec 2006
    First published in Mind Volume LXXIII, Number 289 Pp. 84-96, 1964.
    Abstract (actually the opening paragraph of the paper):
    In ordinary discourse we often use or accept as valid, arguments of the form "P, so Q", or "P, therefore Q", or "Q, because P" where the validity of the inference from P to Q is not merely logical: the statement of the form "If P then Q" is not a logical truth, even if it is true. Inductive inferences and inferences made in the course of moral arguments provide illustrations of this. Philosophers, concerned about the justification for such reasoning, have recently debated whether the validity of these inferences depends on special rules of inference which are not merely logical rules, or on suppressed premisses which, when added to the explicit premisses, yield an argument in which the inference is logically, that is deductively, valid. In a contribution to MIND ("Rules of Inference in Moral Reasoning", July 1961), Nelson Pike describes such a debate concerning the nature of moral reasoning. Hare claims that certain moral arguments involve suppressed deductive premisses, whereas Toulmin analyses them in terms of special rules of inference, peculiar to the discourse of morality. Pike concludes that the main points so far made on either side of the dispute are "quite ineffective" (p. 391), and suggests that the problem itself is to blame, since the reasoning of the "ordinary moralist" is too rough and ready for fine logical distinctions to apply (pp. 398-399). In this paper an attempt will be made to take his discussion still further and explain in more detail why arguments in favour of either rules of inference or suppressed premisses must be ineffective. It appears that the root of the trouble has nothing to do with moral reasoning specifically, but arises out of a general temptation to apply to meaningful discourse a distinction which makes sense only in connection with purely formal calculi.

  114. Filename: colour-incompatibilities.pdf
    Title: Colour Incompatibilities and Analyticity

    Author: Aaron Sloman

    Date Installed: 6 Jan 2010; Published 1964

    Where published:

    Analysis, Vol. 24, Supplement 2. (Jan., 1964), pp. 104-119.
    Abstract: (Opening paragraph)
    The debate about the possibility of synthetic necessary truths is an old and familiar one. The question may be discussed either in a general way, or with reference to specific examples. This essay is concerned with the specific controversy concerning the incompatibility of colours, or colour concepts, or colour words. The essay is mainly negative: I shall neither assume, nor try to prove, that colours are incompatible, or that their incompatibility is either analytic or synthetic, but only that certain more or Less familiar arguments intended to show that incompatibility relations between colours are analytic fail to do so. It will follow from this that attempts to generalise these arguments to show that no necessary truths can be synthetic will be unsuccessful, unless they bring in quite new sorts of considerations. The essay does, however, have a positive purpose, namely the partial clarification of some of the concepts employed by philosophers who discuss this sort of question, concepts such as 'analytic' and 'true in virtue of linguistic rules'. Such clarification is desirable since it is often not at all clear what such philosophers think that they have established, since the usage of these terms by philosophers is often so loose and divergent that disagreements may be based on partial misunderstanding. The trouble has a three-fold source : the meaning of 'analytic' is unclear, the meaning of 'necessary' is unclear, and it is not always clear what these terms are supposed to be applied to. (E.g. are they sentences, statements, propositions, truths, knowledge, ways of knowing, or what?) Not all of these confusions can be eliminated here, but an attempt will be made to clear some of them away by giving a definition of 'analytic' which avoids some of the confused and confusing features of Kant's exposition without altering the spirit of his definition.


  115. Title: Abstract of Functions and Rogators (1965)
    Author: Aaron Sloman
    Date Installed: 23 Dec 2007

    A summary of the 1963 Logic Colloquium was published by E. J. Lemmon, M. A. E. Dummett, and J. N. Crossley with abstracts of papers presented, including my 'Functions and Rogators', was published in The Journal of Symbolic Logic, Vol. 28, No. 3. (Sep., 1963), pp. 262-272. accessible online here.


  116. Filename: sloman-1962 (HTML overview.)
    Title: Oxford University DPhil Thesis (1962): Knowing and Understanding
         Relations between meaning and truth, meaning and necessary truth,
         meaning and synthetic necessary truth
    Author: Aaron Sloman
    In 2016, the thesis chapters were combined to form a freely available machine readable book, in PDF and TXT/HTML formats.
    o Full thesis transcribed (PDF)
    o Full thesis transcribed (html) (Added 6 Jan 2018)
         (Plain text, i.e. no italics/underlining, but with figures added, on pages 287, 288, 307)
    This thesis was scanned in and made generally available by Oxford University Research Archive (at the Bodleian library) in the form of PDF versions of the chapters, in 2007. Those PDF files had only the scanned image content and were viewable and printable, but not searchable. In 2014 a few of the files were converted to text. In 2016, with the help of Luc Beaudoin an Indian company (Hitech) was engaged to retype the remaining chapters. All the chapters are now available in searchable .txt and .pdf forms. Later a free book version containing all the chapters will be made available here. (Email a.sloman if you would like an early copy.)

    The original bulky scanned PDF chapters and also the new PDF and TXT versions are available here, along with more detailed information about the contents, the background to the thesis, and some references to later developments. The contents list of files is in here.

    The scanned PDF (image only) files are also at the Oxford University Bodleian library web site, via this 'permanent ID':

    Date Installed: 2 May 2007 (Last updated 6 Jan 2018)


    The aim of the thesis is to show that there are some synthetic necessary truths, or that synthetic apriori knowledge is possible. This is really a pretext for an investigation into the general connection between meaning and truth, or between understanding and knowing, which, as pointed out in the preface, is really the first stage in a more general enquiry concerning meaning. (Not all kinds of meaning are concerned with truth.) After the preliminaries (chapter one), in which the problem is stated and some methodological remarks made, the investigation proceeds in two stages. First there is a detailed inquiry into the manner in which the meanings or functions of words occurring in a statement help to determine the conditions in which that statement would be true (or false). This prepares the way for the second stage, which is an inquiry concerning the connection between meaning and necessary truth (between understanding and knowing apriori). The first stage occupies Part Two of the thesis, the second stage Part Three. In all this, only a restricted class of statements is discussed, namely those which contain nothing but logical words and descriptive words, such as "Not all round tables are scarlet" and "Every three-sided figure is three-angled". (The reasons for not discussing proper names and other singular definite referring expressions are given in Appendix I.)

    Some of the ideas developed here were expanded in


Maintained by Aaron Sloman.