THE UNIVERSITY OF BIRMINGHAM
School of Computer Science
Cognitive Science Research Centre

THE COGNITION AND AFFECT PROJECT

PROJECT WEB DIRECTORY
PAPERS ADDED IN THE PERIOD 2000-2002 (APPROXIMATELY)

See also

PAPERS 2000 -- 2002 CONTENTS LIST
RETURN TO MAIN COGAFF INDEX FILE

SLIDE PRESENTATIONS ON THE COGAFF TOPICS can be found in http://www.cs.bham.ac.uk/research/projects/cogaff/talks/

Closely related publications are available at the web site of Matthias Scheutz

NOTE

This file is http://www.cs.bham.ac.uk/research/projects/cogaff/00-02.html
Maintained by Aaron Sloman -- who does not respond to Facebook requests.
It contains an index to files in the Cognition and Affect Project's FTP/Web directory produced or published in the period 2000-2002. Some of the papers published in this period were produced earlier and are included in one of the lists for an earlier period http://www.cs.bham.ac.uk/research/cogaff/0-INDEX.html#contents

A list of PhD and MPhil theses was added in June 2003

Last updated: 2 May 2010; 11 Oct 2010; 30 Oct 2010; 13 Nov 2010; 7 Jul 2012


PAPERS IN THE COGNITION AND AFFECT DIRECTORY
Produced or published in the period 2000-2002 (Approximately)
(Latest first)

Most of the papers listed here are in compressed or uncompressed postscript format. Some are latex or plain ascii text. Some of the postscript files are duplicated in PDF format. For information on free browsers for these formats see http://www.cs.bham.ac.uk/~axs/browsers.html

PDF versions of postscript files can be provided on request. Email A.Sloman@cs.bham.ac.uk requesting conversion.


The following Contents list (in reverse chronological order) contains links to locations in this file giving further details, including abstracts, and links to the papers themselves.

JUMP TO DETAILED LIST (After Contents)

CONTENTS -- FILES 2000-2002 (Latest First)

What follows is a list of links to more detailed information about each paper. From there you can select the actual papers, mostly in postscript format, and some also in PDF.

Title: A Framework for Comparing Agent Architectures
Author: Aaron Sloman and Matthias Scheutz

Title: How to derive "better" from "is"
Author: Aaron Sloman

Title: An architecture of diversity for commonsense reasoning.
Authors: McCarthy, John, Minsky, Marvin, Sloman, Aaron, Gong, Leiguang, Lau, Tessa, Morgenstern, Leora, Mueller, Erik T., Riecken, Doug, Singh, Moninder, & Singh, Push

Title: An Anytime Planning Agent For Computer Game Worlds
Author: Nick Hawes

Title: Anytime Planning For Agent Behaviour
Author: Nick Hawes

Title: More things than are dreamt of in your biology: Information processing in biologically-inspired robots.
Author: Aaron Sloman and Ron Chrisley

Virtual Machines and Consciousness
Author: Aaron Sloman and Ron Chrisley

Title: Must Intelligent Systems Be Scruffy?
Author: Aaron Sloman

Title: Reflective Architectures for Damage Tolerant Autonomous Systems.
Author: Catriona Kennedy and Aaron Sloman

Title: Autonomous Recovery from Hostile Code Insertion using Distributed Reflection
Author: Catriona Kennedy and Aaron Sloman

Title: Closed Reflective Networks: a Conceptual Framework for Intrusion-Resistant Autonomous Systems
Author: Catriona Kennedy and Aaron Sloman

Title: The Computer Revolution in Philosophy (1978 book)
Author: Aaron Sloman

Title: The Irrelevance of Turing Machines to AI
Author: Aaron Sloman

Title: Evolvable Biologically Plausible Visual Architectures
Author: Aaron Sloman

Title: Reducing Indifference: Steps towards Autonomous Agents with Human Concerns
Author: Catriona Kennedy

Title: Beyond Shallow Models of Emotion
Author: Aaron Sloman

Title: Varieties of Affect and the CogAff Architecture Schema
Author: Aaron Sloman

Title: Affective vs. Deliberative Agent Control
Author: Matthias Scheutz and Brian Logan

Title: Experiencing Computation: A tribute to Max Clowes
Author: Aaron Sloman

Title: Did Searle attack strong strong or weak strong AI?
Author: Aaron Sloman

Title: DRAFT: A Framework for Comparing Agent Architectures (Now superseded by UKCI'02 paper)
Authors: Aaron Sloman and Matthias Scheutz

Title: Affect and Agent Control: Experiments with Simple Affective States
Authors: Matthias Scheutz and Aaron Sloman

Title: The primacy of non-communicative language
Author: Aaron Sloman

Title: AI as a method? Commentary on Green on AI-Cognitive-Science
Author: Matthias Scheutz

Title: What are virtual machines? Are they real?
Author: Aaron Sloman

Title: Real-Time Goal-Orientated Behaviour for Computer Game Agents
Author: Nick Hawes

Title: Emotional States and Realistic Agent Behaviour
Author: Matthias Scheutz, Aaron Sloman Brian Logan

Title: Interacting Trajectories in Design Space and Niche Space: A philosopher speculates about evolution
Author: Aaron Sloman

Title: Are Turing machines relevant to AI? (Superseded)
Author: Aaron Sloman

Title: How many separately evolved emotional beasties live within us?
Author: Aaron Sloman

Title: Code and Documentation for PhD Thesis: Concern Processing in Autonomous Agents
Author: Steve Allen

Title: Diagrams in the Mind?
Author: Aaron Sloman

Title: Architecture-Based Conceptions of Mind (Final version)
Author: Aaron Sloman

Title: Models of models of mind
Author: Aaron Sloman

Title: Evolvable architectures for human-like minds
Authors: Aaron Sloman and Brian Logan


DETAILS OF FILES AVAILABLE


BACK TO CONTENTS LIST



Filename: sloman-scheutz-ukci02.pdf
Filename: sloman-scheutz-ukci02.ps
Title: A Framework for Comparing Agent Architectures
Revised version of 2001 paper below with same title.
Author: Aaron Sloman and Matthias Scheutz

Originally Published in: Proceedings UKCI'02, UK Workshop on Computational Intelligence, September 2002, Birmingham, UK.

Date Installed here: 22 Dec 2002

Abstract:
Research on algorithms and representations once dominated AI. Recently the importance of architectures has been acknowledged, but researchers have different objectives, presuppositions and conceptual frameworks, and this can lead to confused terminology, argumentation at cross purposes, re-invention of wheels and fragmentation of the research. We propose a methodological framework: develop a general representation of a wide class of architectures within which different architectures can be compared and contrasted. This should facilitate communication and integration across sub-fields of and approaches to AI, as well as providing a framework for evaluating alternative architectures. As a first-draft example we present the CogAff architecture schema, and show how it provides a draft framework. But there is much still to be done.
Keywords: AI architectures, autonomous agents, cognitive modelling, philosophical foundations, software agents, dimensions of variation.




Filename: http://www.cs.bham.ac.uk/research/cogaff/sloman.better.html
Filename: http://www.cs.bham.ac.uk/research/cogaff/sloman-better.pdf
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

Abstract:

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



http://www.research.ibm.com/journal/sj41-3.html
Title: An architecture of diversity for commonsense reasoning.

Authors: John McCarthy, Marvin Minsky, Aaron Sloman, Leiguang Gong, Tessa Lau, Leora Morgenstern, Erik T. Mueller, Doug Riecken, Moninder Singh, and Push Singh,

Published as: 'An architecture of diversity for commonsense reasoning', in IBM Systems Journal, 41(3), pp. 530-539. (2002).

Date: 8 Sep 2002

Abstract:
Although computers excel at certain bounded tasks that are difficult for humans, such as solving integrals, they have difficulty performing commonsense tasks that are easy for humans, such as understanding stories. In this Technical Forum contribution, we discuss commonsense reasoning and what makes it difficult for computers. We contend that commonsense reasoning is too hard a problem to solve using any single artificial intelligence technique. We propose a multilevel architecture consisting of diverse reasoning and representation techniques that collaborate and reflect in order to allow the best techniques to be used for the many situations that arise in commonsense reasoning. We present story understanding specifically, understanding and answering questions about progressively harder children's texts as a task for evaluating and scaling up a commonsense reasoning system.
(Report of a workshop held at the IBM Thomas J. Watson Research Center in March 2002).


Filename: nick.hawes.cg02.pdf
Filename: nick.hawes.cg02.ps
Title: An Anytime Planning Agent For Computer Game Worlds

Authors: Nick Hawes

In Proceedings, Workshop on Agents in Computer Games at The 3rd International Conference on Computers and Games (CG'02), July 27th 2002. Pages 1 -- 14.

Date: 27th July 2002

Abstract:
Computer game worlds are dynamic and operate in real-time. Any agent in such a world must utilize techniques that can deal with these environmental factors. Additionally, to advance past the current state-of-the-art, computer game agents must display intelligent goal-orientated behaviour. Traditional planners, whilst fulfilling the need to generate intelligent, goal-orientated behaviour, fail dramatically when placed under the demands of a computer game environment. This paper introduces A-UMCP, an anytime hierarchical task network planner, as a feasible approach to planning in a computer game environment. It is a planner that can produce intelligent agent behaviour whilst being flexible with regard to the time used to produce plans.


Filename: nick.hawes.plansig01.pdf
Filename: nick.hawes.plansig01.ps
Title: Anytime Planning For Agent Behaviour

In Proceedings, PLANSIG 2001, December 13-14 December 2001. Pages 157 -- 166.

Author: Nick Hawes
Date: December 13-14 December 2001 (Added 9 Aug 2002)

Abstract:
For an agent to act successfully in a complex and dynamic environment (such as a computer game) it must have a method of generating future behaviour that meets the demands of its environment. One such method is anytime planning. This paper discusses the problems and benefits associated with making a planning system work under the anytime paradigm, and introduces Anytime-UMCP (A-UMCP), an anytime version of the UMCP hierarchical task network (HTN) planner. It also covers the necessary abilities an agent must have in order to execute plans produced by an anytime hierarchical task network planner.



Filename: sloman-chrisley-rs.ps
Filename: sloman-chrisley-rs.pdf

Title: More things than are dreamt of in your biology: Information processing in biologically-inspired robots.

Revised version of paper presented at: International Workshop Biologically-Inspired Robotics: The Legacy of W.Grey Walter, 14-16 August 2002, Bristol, UK http://www.ecs.soton.ac.uk/~rid/wgw02/home.html

Author: Aaron Sloman and Ron Chrisley
Date installed: 1 Jul 2002 (Revised 12 May 2003, 6 Aug 2004)
NOTE:The original version has been removed.
This entry now points to the version installed on 6th Aug 2004, referenced in http://www.cs.bham.ac.uk/research/cogaff/04.html#200408

Abstract:
This paper is concerned with some methodological and philosophical problems related both to the long-term objective of building human-like robots (like those `in the movies') and short- and medium-term objectives of building robots with capabilities of more or less intelligent animals. In particular, we claim that organisms are information-processing machines, and thus information-processing concepts will be essential for designing biologically-inspired robots. However, identifying relevant concepts is non-trivial since what an information-processor is doing cannot in general be determined by using the standard observational techniques of the physical sciences. Having a general framework for describing and comparing agent architectures may help.
Keywords: Architecture, biology, evolution, information-processing, ontology, ontological blindness, robotics, virtual machines


Filename: sloman-chrisley-jcs.ps
Filename: sloman-chrisley-jcs.pdf

Title: Virtual Machines and Consciousness

Original version submitted for publication in 2002. Now out of date. Final version is in http://www.cs.bham.ac.uk/research/cogaff/03.html#03-02

Author: Aaron Sloman and Ron Chrisley
Date Originally installed: 22 May 2002

Abstract:
See new version.

NOTE

This is an expanded version of talk 9 at http://www.cs.bham.ac.uk/research/projects/cogaff/talks/#talk9


Filename: sloman.scruffy.ai.ps
Filename: sloman.scruffy.ai.pdf

Title: Must Intelligent Systems Be Scruffy?

Presented at Evolving Knowledge Conference. Reading University Sept 1989
In Evolving Knowledge in Natural Science and Artificial Intelligence, Eds J.E.Tiles, G.T.McKee, G.C.Dean, London: Pitman, 1990
Comments to: A.Sloman@cs.bham.ac.uk

Author: Aaron Sloman
Date installed: 22 Feb 2002. Originally published 1990
Plain text (troff) version here: http://www.cs.bham.ac.uk/research/projects/cogaff/misc/scruffy.ai.text

Abstract:
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


Filename: kennedy.sloman.CSR-02-01.ps
Filename: kennedy.sloman.CSR-02-01.pdf

Title: Reflective Architectures for Damage Tolerant Autonomous Systems.

Also technical report number CSR-02-1 School of Computer Science, The University of Birmingham.
Comments to: C.M.Kennedy@cs.bham.ac.uk

Author: Catriona Kennedy and Aaron Sloman
Date installed: 21 Feb 2002

Abstract:
Most existing literature on reflective architectures is concerned with language interpreters and object-oriented programming methods. In contrast, there is little work on reflective architectures which enable an {\it autonomous system} to have these types of access to its own operation for the purpose of survival in a hostile environment. Using the principles of natural immune systems, we present an autonomous system architecture which first acquires a model of its own normal operation and then uses this model to detect and repair faults and intrusions (self/nonself discrimination in immune systems). To enable the system to repair damage in {\it any} part of its operation, including its monitoring and repair mechanisms, the architecture is distributed so that all components are monitored by some other component within the system. We have distributed the system in the form of mutually protecting agents which monitor and repair each other's self-protection mechanisms. This paper presents the first version of a prototype implementation in which only omission failures occur.


Filename: kennedy.sloman.CSR-02-02.ps
Filename: kennedy.sloman.CSR-02-02.pdf

Title: Autonomous Recovery from Hostile Code Insertion using Distributed Reflection

Also technical report number CSR-02-2 School of Computer Science, The University of Birmingham
Comments to: C.M.Kennedy@cs.bham.ac.uk

Author: Catriona Kennedy and Aaron Sloman
Date installed: 21 Feb 2002

Abstract:
In a hostile environment, an autonomous system requires a reflective capability to detect problems in its own operation and recover from them without external intervention. We present an architecture in which reflection is distributed so that components mutually observe and protect each other, and where the system has a distributed model of all its components, including those concerned with the reflection itself. Some reflective (or ``meta-level'') components enable the system to monitor its execution traces and detect anomalies by comparing them with a model of normal activity. Other components monitor ``quality'' of performance in the application domain. Implementation in a simple virtual world shows that the system can recover from certain kinds of hostile code attacks that cause it to make wrong decisions in its application domain, even if some of its self-monitoring components are also disabled.


Filename: kennedy.sloman.CSR-02-03.ps
Filename: kennedy.sloman.CSR-02-03.pdf

Title: Closed Reflective Networks: a Conceptual Framework for Intrusion-Resistant Autonomous Systems

Also technical report number CSR-02-3 School of Computer Science, The University of Birmingham
Comments to: C.M.Kennedy@cs.bham.ac.uk

Author: Catriona Kennedy and Aaron Sloman
Date installed: 21 Feb 2002

Abstract:
Intrusions may sometimes involve the insertion of hostile code in an intrusion-detection system, causing it to ``lie'', for example by giving a flood of false-positives. To address this problem we consider an intrusion detection system as a reflective layer in an autonomous system which is able to observe the whole system's internal behaviour and take corrective action as necessary. To protect the reflective layer itself, several mutually reflective components (agents) are used within the layer. Each agent acquires a model of the normal behaviour of a group of other agents under its protection and uses this model to detect anomalies. The ideal situation is a ``closed reflective network'' where all components are monitored and protected by other components within the same autonomous system, so that no component is left unprotected.

Using informal rapid-prototyping we implemented a closed reflective network based on three agents, where the agents use majority voting to determine if an intrusion has occurred and whether a response is required. The main conclusion is that such a network may be better implemented on multiple hardware processors connected together as a simple neural network.


Filename: http://www.cs.bham.ac.uk/research/cogaff/crp/

Title: THE COMPUTER REVOLUTION IN PHILOSOPHY:
Philosophy, science and models of mind.

Originally published by Harvester Press and Humanities Press in 1978, but long since out of print. Now available online free of charge, with additional notes and some re-drawn images, with a Creative Commons Attribution 2.5 Generic 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 chapers have had additional notes and comments added, all clearly marked as new.
Author: Aaron Sloman
Date installed: 29 Sep 2001
Last updated: 18 Dec 2011 (Ebook Version available, via Sergei Kaunov)

Abstract:
See the contents list

Note added 18 Dec 2011

Sergei Kaunov has converted this book to Amazon kindle format. It is now available for download at a very low cost (the minimum allowed by Amazon):
(USD$2.06) from http://www.amazon.com/dp/B006JT8FSK
or for GBP £1.32 from
http://www.amazon.co.uk/Computer-Revolution-Philosophy-science-ebook/dp/B006JT8FSK/ref=kinw_dp_ke?ie=UTF8&m=A3TVV12T0I6NSM

It is also available for download at no cost from these locations:

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."

Note added 4 Oct 2007

I have discovered that a review of 'The Computer Revolution in Philosophy' by Douglas Hofstander is available online here.
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY
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 in AI he 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 more about the world and themselves.)


Filename: sloman.turing.irrelevant.ps
Filename: sloman.turing.irrelevant.pdf

Title: The Irrelevance of Turing Machines to AI

In Computationalism: New Directions, Ed Matthias Scheutz pages 87--127, Cambridge, MA, MIT Press, 2002. http://www.nd.edu/~mscheutz/publications/scheutz02mitbook.html

Author: Aaron Sloman
Date installed: 13 Jul 2001

Abstract:
The common view that the notion of a Turing machine is directly relevant to AI is criticised. It is argued that computers are the result of a convergence of two strands of development with a long history: development of machines for automating various physical processes and machines for performing abstract operations on abstract entities, e.g. doing numerical calculations. Various aspects of these developments are analysed, along with their relevance to AI, and the similarities between computers viewed in this way and animal brains. This comparison depends on a number of distinctions: between energy requirements and information requirements of machines, between ballistic and online control, between internal and external operations, and between various kinds of autonomy and self-awareness. The ideas are all intuitively familiar to software engineers, though rarely made fully explicit. Most of this has nothing to do with Turing machines or most of the mathematical theory of computation. But it has everything to do with both the scientific task of understanding, modelling or replicating human or animal intelligence and the engineering applications of AI, as well as other applications of computers.


Filename: sloman.bmvc01.ps
Filename: sloman.bmvc01.pdf

Also available at http://www.bmva.ac.uk/bmvc/2001/papers/120/120.html

Title: Evolvable Biologically Plausible Visual Architectures

in Proceedings of British Machine Vision Conference, Manchester, Sept 2001.
Online at http://www.bmva.ac.uk/bmvc/2001/

Conference web site originally at: http://www.bmvc2001.man.ac.uk/


Author: Aaron Sloman
Date installed: 8 Sep 2001 (revised format)

Abstract:
Much work in AI is fragmented, partly because the subject is so huge that it is difficult for anyone to think about all of it. Even within sub-fields, such as language, reasoning, and vision, there is fragmentation, as the sub-sub-fields are rich enough to keep people busy all their lives. However, there is a risk that results of isolated research will be unsuitable for future integration, e.g. in models of complete organisms, or human like robots. This paper offers a framework for thinking about the many components of visual systems and how they relate to the whole organism or machine. The viewpoint is biologically inspired, using conjectured evolutionary history as a guide to some of the features of the architecture. It may also be useful both for modelling animal vision and designing robots with similar capabilities.


Filename: kennedy.ethics.pdf
Filename: kennedy.ethics.ps

Title: Reducing Indifference: Steps towards Autonomous Agents with Human Concerns

in Proceedings of the Symposium "AI, Ethics and (Quasi-) Human Rights" at the 2000 Convention of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB'00), Birmingham, April 2000.

Author: C. Kennedy
Date installed: 29 Jun 2001

Abstract:
In this paper, we consider a hypothetical software agent that informs users of possible human rights violations by scanning relevant new reports. Such an agent suffers from the ``indifference'' problem if it allows the definition of human rights in its knowledge base to be arbitrarily modified. We do not believe that embodiment in the human world is necessary to overcome this problem. Instead, we propose that a {\it reflective architecture} is required so that the agent can protect the integrity of its knowledge base and underlying software mechanisms. Furthermore, the monitoring coverage must be {\it sufficient} so that the reflective mechanisms themselves are also monitored and protected. To avoid the problem of infinite regress, we are exploring a biologically inspired form of {\it distributed} reflection, where the agent's functionality is distributed over several ``micro-level'' agents. These agents mutually acquire models of each other and subsequently use their models to observe and repair each other; in particular, they look for deviations from normal execution patterns (anomalies). We present a working architecture which solves a restricted version of the indifference problem in a simple virtual world. Finally, we give a conceptual outline of how this architecture can be applied in the human rights scenario.


Filename: sloman.iqcs01.pdf
Filename: sloman.iqcs01.ps

Title: Beyond Shallow Models of Emotion

In Cognitive Processing, Vol 2, No 1, 2001, pp 177-198 (Summer 2001).

This is an extended version of the paper with the same name presented at I3 Spring Days Workshop on Behavior planning for life-like characters and avatars Sitges, Spain, March 1999)


Author: Aaron Sloman
Date installed: 12 May 2001

Abstract:
There is a huge diversity of definitions of ``emotion'' some of which are associated with relatively shallow behavioural or measurable criteria or introspectable experiences, for instance use of facial expression, physiological measures, activity of specific regions of the brain, or the experience of bodily changes or desires, such as wanting to run away, or to hurt someone. There are also deeper theories that link emotional states to a variety of mechanisms within an information processing architecture that are not easily observable or measurable, not least because they are components of virtual machines rather than physical or physiological mechanisms. We can compare this with ``shallow'' definitions of chemical compounds such as salt, sugar, or water, in terms of their appearance and observed behaviours in various test situations, and their definitions in the context of a theory of the architecture of matter which is mostly concerned with postulated sub-atomic entities and and a web of relationships between them which cannot easily be observed, so that theories about them are not easily confirmed or refuted. This paper outlines an approach to the search for deeper explanatory theories of emotions and many other kinds of mental phenomena, which includes an attempt to define the concepts in terms of the underlying information processing architectures and the classes of states and processes that they can support. A serious problem with this programme is the difficulty of finding good constraints on theories, since in general observable facts are consistent with infinitely many explanatory mechanisms. This ``position paper'' offers as a partial solution the requirement that proposed architectures be capable of having been produced by biological evolution, in addition to being subject to constraints such as implementability in known biological mechanisms, various resource limits (time, memory, energy, etc.) and being able to account for a wide range of human functionality. Within such an architecture-based theory we can distinguish (at least) primary emotions, secondary emotions, and tertiary emotions, and produce a coherent theory which explains a wide range of phenomena and also partly explains the diversity of theories: most theorists focus on only a subset of types of emotions, like the proverbial blind men trying to say what an elephant is on the basis of feeling only a leg, an ear, a tusk, the trunk, etc.


Filename: sloman-aisb01.pdf
Filename: sloman-aisb01.ps

Title: Varieties of Affect and the CogAff Architecture Schema
A paper for the Symposium on Emotion, Cognition, and Affective Computing at the AISB'01 Convention, 21st - 24th March 2001.
Author: Aaron Sloman
Date installed: 2 Mar 2001

Abstract:
In the last decade and a half, the study of affect in general and emotion in particular has become fashionable in scientific psychology, cognitive science and AI, both for scientific purposes and for the purpose of designing synthetic characters in games and entertainments. Such work understandably starts from concepts of ordinary language (e.g. ``emotion'', ``feeling'', ``mood'', etc.). However, these concepts can be deceptive: they appear to have clear meanings but are used in very imprecise and systematically ambiguous ways. This is often because of explicit or implicit theories about mental states and process. In the Cognition and Affect project we have been attempting to explore the benefits of developing architecture-based concepts, i.e. starting with specifications of architectures for complete agents and then finding out what sorts of states and processes are supported by those architectures. So, instead of presupposing one theory of the architecture and explicitly or implicitly basing concepts on that, we define a space of architectures generated by the CogAff architecture schema, where each theory supports different collections of concepts. In that space we focus on one architecture H-Cogaff, a particularly rich instance of the CogAff architecture schema, conjectured as a theory of human information processing. The architecture-based concepts that it supports provide a framework for defining with greater precision than previously a host of mental concepts, including affective concepts. We then find that these map more or less loosely onto various pre-theoretical concepts, such as ``emotion'', etc. We indicate some of the variety of emotion concepts generated by the H-Cogaff architecture A different architecture might be appropriate for exploring affective states of insects, or reptiles, or other mammals, or even young children.


Filename: scheutz-logan-aisb01.pdf
Filename: scheutz-logan-aisb01.ps

Title: Affective vs. Deliberative Agent Control
A paper for the Symposium on Emotion, Cognition, and Affective Computing at the AISB'01 Convention, 21st - 24th March 2001, extending the "GAME-ON 2000" paper below.
Authors: Matthias Scheutz (Birmingham) and Brian Logan (Nottingham)
Date installed: 2 Mar 2001

Abstract:
In this paper, we outline a research strategy for analysing the properties of different agent architectures, in particular the cognitive and affective states/processes they can support. We demonstrate this architecture-based research strategy, which effectively views cognitive and affective states as architecture-dependent, with an example of a simulated multi-agent environment, where agents with different architectures have to compete for survival. We show that agents with ``affective'' and ``deliberative'' capabilities do best in different kinds of environments and briefly discuss the implications of combining affective and deliberative capabilities in a single architecture. We argue that such explorations of the trade-offs of alternative architectures will help us understand the role of affective processes in agent control and reasoning, and may lead to important new insights in the attempt to understand natural intelligence and evolutionary trajectories.


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) (Updated 13 Apr 2014)

Abstract:
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 the 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 in Computing in Schools, and was later re-published in New horizons in educational computing, Ed. Masoud Yazdani, 1984, pp. 207--219, (Ellis Horwood Series In Artificial Intelligence.)

The version installed here in 2001, had some footnotes added, referring to subsequent developments influenced by the work or ideas of Max Clowes.

In March 2014, a personal recollection and tribute from Wendy Manktellow (Nee Taylor) was added as an appendix.
http://www.cs.bham.ac.uk/research/projects/cogaff/sloman-clowestribute.html#wendy

In April 2014 I added a draft annotated biography and list of publications of Max Clowes, also as an appendix
http://www.cs.bham.ac.uk/research/projects/cogaff/sloman-clowestribute.html#bio
making use of information found on the internet, on my bookshelves, or supplied by former colleagues and students.
There are several gaps, so contributions to fill those gaps will be much appreciated -- also electronic copies of papers by Max Clowes not already indicated as being available online.


Filename: sloman.searle.85.pdf
Filename: sloman.searle.85.ps
Filename: sloman.searle.85.text

Title: Did Searle attack strong strong or weak strong AI?
(Originally appeared 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 installed: 13 Jan 2001 (Originally published 1985)
(Added Postscript and PDF versions 23 Oct 2005)

Abstract:
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.


Filename: sloman.scheutz.framework.ps
Filename: sloman.scheutz.framework.pdf

Title: DRAFT: A Framework for Comparing Agent Architectures
{\bf NB} now superseded by UKCI'02 paper
Authors: Aaron Sloman and Matthias Scheutz
Date: 9 Jan 2001 (Revised on 1 Jul 2002)

Abstract:
Research on algorithms and representations once dominated AI. Recently the importance of architectures has been acknowledged, but researchers have different objectives, presuppositions and conceptual frameworks, and this, can lead to confused terminology, argumentation at cross purposes, re-invention of wheels and fragmentation of the research. We propose a methodological framework: develop a representation of a general class of architectures within which different architectures can be compared and contrasted. This should facilitate communication and integration across sub-fields of and approaches to AI, as well providing a framework for evaluating alternative architectures. As a first-draft example we present the CogAff architecture schema, and show how it provides a draft framework. But there is much still to be done.


Filename: scheutz.sloman.affect.control.ps
Filename: scheutz.sloman.affect.control.pdf

Title: Affect and Agent Control: Experiments with Simple Affective States
Affect and Agent Control: Experiments with Simple Affective States. In Ning Zhong et al. (Eds.) Intelligent Agent Technology: Research and Development. World Scientific Publisher: New Jersey, 200-209.
Presented at IAT01 International Conference on Intelligent Agent Technology, Japan, October 2001.
Authors: Matthias Scheutz and Aaron Sloman
Date: 3rd July 2001

Abstract:
In this paper we analyze functional roles of affective states in agent control in relatively simple agents in a variety of environments. The analysis is complemented by various simulation experiments in a competitive multi-agent environment, which show that simple affective states (like ``hunger'') can be very effective in agent control and are likely to evolve even in competitive environments. This illustrates the methodology of exploring neighbourhoods in ``design space'' in order to understand tradeoffs in the development of different kinds of agent architectures, whether natural or artificial.
Keywords: Artificial life, AI architectures, multiagent systems, philosophical foundations.


Filename: sloman.primacy.inner.language.pdf
Filename: sloman.primacy.inner.language.ps
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

Abstract:
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.


Filename: http://www.cogsci.soton.ac.uk/cgi/psyc/newpsy?11.097

Title: AI as a method? Commentary on Green on AI-Cognitive-Science
In Psycoloquy: 11(097)
Author: Matthias Scheutz
Date: 26 Oct 2000

Abstract:
In his target article "Is AI the right method for cognitive science?" Green (2000) wants to establish that results in AI have little or no explanatory value for psychology and cognitive science as AI attempts to "simulate something that is not, at present, at all well understood". While Green is right that the foundations of psychology are still insufficiently worked out, there is no reason for his pessimism, which rests on a misconception of AI. AI properly understood can be seen to contribute to the clarification of foundational issues in psychology and cognitive science.

REF
Green, C.D. (2000) Is AI the Right Method for Cognitive Science? PSYCOLOQUY 11(061)
ftp://ftp.princeton.edu/pub/harnad/Psycoloquy/2000.volume.11/psyc.00.11.061.ai-cognitive-science.1.green
http://www.cogsci.soton.ac.uk/cgi/psyc/newpsy?11.061


Filename: sloman.virtual.slides.pdf
Filename: sloman.virtual.slides.ps

Title: What are virtual machines? Are they real?
Slides for seminar presented on 12th Sept., 2000.
Author: Aaron Sloman
Date: 16 Oct 2000 (Updated 17 Feb 2001 - but still a draft)

Abstract:
Philosophers have long discussed the relationship between mental phenomena and physical phenomena. Theories about this include various types of dualism (there are two kinds of stuff), various types of monism (there's only one kind of stuff), pluralism/polyism (there are many kinds of stuff), each of which has its own variants. E.g. according to one sort of dualism, epiphenomenalism, causal traffic is one-way: physical events can cause mental events and processes but not vice versa, because the physical realm is "causally closed." There seem to be only two options: the only ``true reality'' is the physical world and either everything else is just an interpretation of it, or else its just a collection of ``powerless shadows''. Both views are hard to square with common sense.

Computer scientists and software engineers can now help philosophers sort out this mess. We can make progress because there is a new type of non-physical realm which we understand, because we have created it: the realm of virtual machines in computers. However much of this know-how is still at the stage of a "craft", i.e. it is mostly intuitions and practical know-how of engineers and designers, though theory is in hot pursuit.

Virtual machines have components which interact causally and change over time. When they run they produce many sorts of physical effects, e.g. changes on the screen and in the computer's memory, or movements of a robot's limbs. How is that possible if the underlying physical circuitry is causally closed?

Maybe our notions of causation become deeply confused when we address questions about causal closure. My conjecture is that by understanding more clearly what we mean by "X caused Y" in the context of these "simple" computational virtual machines we may begin to get a deeper understanding of all sorts of older, vastly more complex and subtle, biological, social, mental, virtual machines and how their reality, and their causal powers, do not contradict anything in physics. They are not an illusion, not just an arbitrary interpretation of the physical world, not ghostly powerless shadows. Philosophy needs help from software engineers in order to understand all this.


Filename: nick.hawes.gameon2000.ps
Filename: nick.hawes.gameon2000.pdf

Title: Real-Time Goal-Orientated Behaviour for Computer Game Agents

Author: Nick Hawes
Date: 29 Sep 2000

Abstract: To increase the depth and appeal of computer games, the intelligence of the characters they contain needs to be increased. These characters should be played by intelligent agents that are aware of how goals can be achieved and reasoned about. Existing AI methods struggle in the computer game domain because of the real-time response required from the algorithms and restrictive processor availability. This paper discusses the CogAff architecture as the basis for an agent that can display goal orientated behaviour under real-time constraints. To aid performance in real-time domains (e.g. computer games) it is proposed that both the processes encapsulated by the architecture, and the information it must operate on should be structured in a way that encourages a fast yet flexible response from the agent. In addition, anytime algorithms are discussed as a method for planning in real-time.


Filename: scheutz-sloman-logan-gameon.pdf
Filename: scheutz-sloman-logan-gameon.ps
Filename: scheutz-sloman-logan-gameon.doc

Title: Emotional States and Realistic Agent Behaviour
Author: Matthias Scheutz, Aaron Sloman, Brian Logan Published/Presented: In Proceedings GAME-ON 2000, Imperial College London, 11-12 Nov 2000, http://hobbes.rug.ac.be/~scs/conf/gameon2000
Date: 26 Sep 2000

Abstract:
In this paper we discuss some of the relations between cognition and emotion as exemplified by a particular type of agent architecture, the CogAff agent architecture. We outline a strategy for analysing cognitive and emotional states of agents along with the processes they can support, which effectively views cognitive and emotional states as architecture-dependent. We demonstrate this architecture-based research strategy with an example of a simulated multi-agent environment, where agents with different architectures have to compete for survival and show that simple affective states can be surprisingly effective in agent control under certain conditions. We conclude by proposing that such investigations will not only help us improve computer entertainments, but that explorations of alternative architectures in the context of computer games may also lead to important new insights in the attempt to understand natural intelligence and evolutionary trajectories.


Filename: sloman.ppsn00.pdf
Filename: sloman.ppsn00.ps

Title: Interacting Trajectories in Design Space and Niche Space: A philosopher speculates about evolution

Authors: Aaron Sloman
Invited keynote talk, PPSN200, Paris, Sept 2000, http://www.inria.fr/ppsn2000
in Parallel Problem Solving from Nature -- PPSN VI
Eds: Marc Schoenauer, Kalyanmoy Deb, Gu"nter Rudolph, Xin Yao, Evelyne Lutton, Juan Julian Merelo, Hans-Paul Schwefel,
Springer: Lecture Notes in Computer Science, No 1917, 2000
pp. 3--16
Date: 26 Sep 2000

Abstract:
There are evolutionary trajectories in two different but related spaces, \emph{design space} and \emph{niche space}. Co-evolution occurs in parallel trajectories in both spaces, with complex feedback loops linking them. As the design of one species evolves, that changes the niche for others and vice versa. In general there will never be a unique answer to the question: does this change lead to higher fitness? Rather there will be tradeoffs: the new variant is better in some respects and worse in others. Where large numbers of mutually interdependent species (designs) are co-evolving, understanding the dynamics can be very difficult. If intelligent organisms manipulate some of the mechanisms, e.g. by mate selection or by breeding other animals or their own kind, the situation gets even more complicated. It may be possible to show how some aspects of the evolution of human minds are explained by all these mechanisms.


http://www.cs.bham.ac.uk/research/projects/cogaff/misc/turing-relevant.html

Title: Are Turing machines relevant to AI? (superseded)
Author: Aaron Sloman
Date: 27 May 2000 Now superseded by version dated 13 Jul 2001

Abstract:
It is often assumed, especially by people who attack AI, that the concept of a Turing machine and the concept of computation defined in terms of Turing computability (or mathematically equivalent notions) are crucial to the role of computers in AI and Cognitive Science, especially so-called "good old fashioned AI" (or GOFAI, a term which is often used by people who have read only incomplete and biased accounts of the history of AI).

It is also often assumed that the notion of computation is inherently linked with Turing machines, with a collection of mathematically equivalent concepts (e.g. a class of recursive functions) and with logic.

In this paper I shall try to show that these assumptions are incorrect, at least as regards the most common ways of thinking about and using computers. I shall try to clarify what it was about computers in the early days (e.g. by around 1960, or earlier) that made them eminently suitable, unlike previous physical man-made machines, for use as a basis for cognitive modelling and for building thinking machines, and also as a catalyst for new theoretical ideas about how minds work.

I think it had little to do with Turing machines, or with predicate logic, but was a result of natural developments of two pre-existing threads in the history of technology. The first thread is concerned with the production and use of calculating machines to perform arithmetical operations. The second, probably more important thread, was the development of mechanisms to control the behaviour of physical machines, such as textile weaving machines.

NOTE: this is a draft discussion note which will probably be re-written extensively in the light of comments and criticisms. It is made accessible here in order to invite criticisms.


Filename: sloman.vienna99.ps
Filename: sloman.vienna99.pdf

Title: How many separately evolved emotional beasties live within us?
Published/Presented: Revised version of Invited Talk: at workshop on Emotions in Humans and Artifacts Vienna, August 1999
To appear in Emotions in Humans and Artifacts, Eds Robert Trappl, Paolo Petta, and Sabine Payr, MIT Press, Cambridge MA., 2002
Author: Aaron Sloman
Date: 27 May 2000 (Revised: 8 Sep 2006}

The version installed here on 8th September 2006 has a few minor changes, including using the word 'CogAff' as a label for an architecture schema not an architecture, using the label 'H-cogaff' for the special case of the proposed human-like architecture, using 'ecosystem' instead of 'ecology', and an improved version of figure 11.

Abstract:
A problem which bedevils the study of emotions, and the study of consciousness, is that we assume a shared understanding of many everyday concepts, such as `emotion', `feeling', `pleasure', `pain', `desire', `awareness', etc. Unfortunately, these concepts are inherently very complex, ill-defined, and used with different meanings by different people. Moreover this goes unnoticed, so that people think they understand what they are referring to even when their understanding is very unclear. Consequently there is much discussion that is inherently vague, often at cross-purposes, and with apparent disagreements that arise out of people unwittingly talking about different things. We need a framework which explains how there can be all the diverse phenomena that different people refer to when they talk about emotions and other affective states and processes. The conjecture on which this paper is based is that adult humans have a type of information-processing architecture, with components which evolved at different times, including a rich and varied collection of components whose interactions can generate all the sorts of phenomena that different researchers have labelled ``emotions''. Within this framework we can provide rational reconstructions of many everyday concepts of mind. We can also allow a variety of different architectures, found in children, brain damaged adults, other animals, robots, software agents, etc., where different architectures support different classes of states and processes, and therefore different mental ontologies. Thus concepts like `emotion', `awareness', etc. will need to be interpreted differently when referring to different architectures. We need to limit the class of architectures under consideration, since for any class of behaviours there are indefinitely many architectures which can produce those behaviours. One important constraint is to consider architectures which might have been produced by biological evolution. This leads to the notion of a human architecture composed of many components which evolved under the influence of the other components as well as environmental needs and pressures. From this viewpoint, a mind is a kind of {\em ecosystem} (previously described as an `ecology') of co-evolved sub-organisms acquiring and using different kinds of information and processing it in different ways, sometimes cooperating with one another and sometimes competing. Within this framework we can hope to study not only mechanisms underlying affective states and processes, but also other mechanisms which are often studied in isolation, e.g. vision, action mechanisms, learning mechanisms, `alarm' mechanisms, etc. We can also explain why some models, and corresponding conceptions of emotion, are shallow whereas others are deeper. Shallow models may be of practical use, e.g. in entertainment and interface design. Deeper models are required if we are to understand what we are, how we can go wrong, etc. This paper is a snapshot of a long term project addressing all these issues.


Filename: http://www.cs.bham.ac.uk/research/poplog/abbott

Title: Code and Documentation for PhD Thesis: Concern Processing in Autonomous Agents
Author: Steve Allen
Date: 27 May 2000

Abstract:
The directory above gives pointers to the code for Steve Allen's Abbott system, and links to his PhD thesis Concern Processing in Autonomous Agents, submitted in February 2000.


Filename: sloman.diagbook.ps
Filename: sloman.diagbook.pdf

Title: Diagrams in the mind?
Published/Presented: Revised version of Invited Talk: Thinking With Diagrams Conference, Aberystwyth, 1998,
In Diagrammatic Representation and Reasoning Eds. M. Anderson, B. Meyer, P. Olivier, Springer-Verlag, (2002)
Author: Aaron Sloman
Date Added: 11 Apr 2000

Abstract:
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 is going on. In particular we need to explain how people understand spatial structure and motion, and how we can think about objects in terms of a basic topological structure with more or less additional metrical information. I shall try to explain why 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, such as infinite ordinals. More questions are asked than answered.

Norman Foo enjoyed this paper.
Search for 'Deductive Reasoning' in his 'Jokes' web site: http://www.cse.unsw.edu.au/~norman/JOKES.html


Filename: sloman-lmpsfinal.ps
Filename: sloman-lmpsfinal.pdf

Title: Architecture-Based Conceptions of Mind (Final version)
(Invited talk at 11th International Congress of Logic, Methodology and Philosophy of Science, Cracow, Poland August 20-26, 1999. Published in: P. Gardenfors and K. Kijania-Placek and J. Wolenski, Eds., In the Scope of Logic, Methodology, and Philosophy of Science (Vol II), (Synthese Library Vol. 316), Kluwer, Dordrecht, pp. 403--427, 2002.
Author: Aaron Sloman
Date: 1 Apr 2000

Slide presentation (2-up): Sloman.cracow.slides.2page.pdf (PDF)

Abstract:
It is argued that our ordinary concepts of mind are both implicitly based on architectural presuppositions and also cluster concepts. By showing that different information processing architectures support different classes of possible concepts, and that cluster concepts have inherent indeterminacy that can be reduced in different ways for different purposes we point the way to a research programme that promises important conceptual clarification in disciplines concerned with what minds are, how they evolved, how they can go wrong, and how new types can be made, e.g. philosophy, neuroscience, psychology, biology and artificial intelligence.


Filename: sloman.dam00intro.ps
Filename: sloman.dam00intro.pdf

Title: Models of models of mind
Programme Chair's introduction to booklet of papers for the Symposium on How to Design a Functioning Mind, at the AISB'00 convention, at Birmingham University, April 17-20, 2000.
Author: Aaron Sloman
Date: 24 Mar 2000

Abstract:
Many people are working on architectures of various kinds for intelligent agents. However different objectives, presuppositions, techniques and conceptual frameworks (ontologies) are used by different researchers. These differences together with the fact that many of the words and phrases of ordinary language used to refer to mental phenomena are radically ambiguous, or worse, indeterminate in meaning, leads to much argumentation at cross purposes, misunderstanding, re-invention of wheels (round and square) and fragmentation of the research community. It was hoped that this symposium would bring together many different sorts of researchers, along with a well known novelist with ideas about consciousness, who might, together, achieve something that would not happen while they continued their separate ways. This introduction sets out a conceptual framework which it is hoped will help that communication and integration to occur. That includes explaining some of the existing diversity and conceptual confusion and offering some dimensions for comparing architectures.


Filename: SlomanLogan.toyota.ps
Filename: SlomanLogan.toyota.pdf

Title: Evolvable architectures for human-like minds
In Affective Minds, Ed. Giyoo Hatano, Elsevier, October 2000
Invited talk at 13th Toyota Conference, on ``Affective Minds'' Nagoya Japan, Nov-Dec 1999
Authors: Aaron Sloman and Brian Logan
Date: 2 Feb 2000

Abstract:
There are many approaches to the study of mind, and much ambiguity in the use of words like `emotion' and `consciousness'. This paper adopts the design stance, in an attempt to understand human minds as information processing virtual machines with a complex multi-level architecture whose components evolved at different times and perform different sorts of functions. A multi-disciplinary perspective combining ideas from engineering as well as several sciences helps to constrain the proposed architecture. Variations in the architecture should accommodate infants and adults, normal and pathological cases, and also animals. An analysis of states and processes that each architecture supports provides a new framework for systematically generating concepts of various kinds of mental phenomena. This framework can be used to refine and extend familiar concepts of mind, providing a new, richer, more precise theory-based collection of concepts. Within this unifying framework we hope to explain the diversity of definitions and theories and move towards deeper explanatory theories and more powerful and realistic artificial models, for use in many applications, including education and entertainment.


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