`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.
PAPERS 1981 -- 1995 CONTENTS LIST
RETURN TO MAIN COGAFF INDEX FILE
This file is
http://www.cs.bham.ac.uk/research/projects/cogaff/81-95.html
Maintained by Aaron Sloman -- who does
not respond to Facebook requests.
It contains an index to files in the Cognition and Affect project
FTP/Web
directory. It contains papers written before 1996.
Some of the papers by Aaron Sloman listed here were written while he was at the University of Sussex. He moved to the University of Birmingham in July 1991.
Last updated: 3 Jan 2010; 13 Nov 2010; 7 Jul 2012
Most of the papers listed here are in compressed or uncompressed
postscript format. Some are latex or plain ascii text. Most are also
available in PDF.
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. Please Email A.Sloman@cs.bham.ac.uk requesting conversion.
Papers are listed below roughly in reverse chronological order.
Title: What Are The Purposes Of Vision?
(link to another file)
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 (Installed here: 4 Nov 2012)
Developing concepts of consciousness
(Commentary on Velmans, BBS, 1991)
Author:
Aaron Sloman (Installed here: 4 Jun 2013)
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 (Installed here: 9 Oct 2012)
Title: A Personal View Of Artificial Intelligence
Preface to Computers and Thought 1989 (by Sharples et al).
Author: Aaron Sloman (Installed here: 4 Sep 2012)
Towards a Computational Theory of Mind (PDF)
Aaron Sloman
(First published 1984 -- installed here with a new end-note 8 Aug
2012. Details in another file.)
Title: Skills Learning and Parallelism
Cognitive Science Conference, 1981
Author: Aaron Sloman
Title: Simulating agents and their environments
Authors: Darryl Davis, Aaron Sloman and Riccardo Poli
Title: Towards a Grammar of Emotions
Author: Aaron Sloman
Title: Beginners Need Powerful Systems
Author: Aaron Sloman
Title: The Evolution of Poplog and Pop-11 at Sussex University
Author: Aaron Sloman
Title: The primacy of non-communicative language
Author: Aaron Sloman
Title: A Philosophical Encounter
Authors: Aaron Sloman
Title: Exploring design space and niche space
Authors: Aaron Sloman
Title: A Hybrid Trainable Rule-based System
Authors: Riccardo Poli and Mike Brayshaw
Title: Information about the SIM_AGENT toolkit
Authors: Aaron Sloman and Riccardo Poli
Title: Goal processing in autonomous agents
Author: Luc P. Beaudoin
Title: Why robots will have emotions
Authors: Aaron Sloman and Monica Croucher
Title: An Emotional Agent -- The Detection and Control of Emergent
Author: Ian Wright
Title: Computational Constraints on Associative Learning,
Author: Edmund Shing
Title: Geneva Emotion Week 1995
Title: Towards a general theory of representations
Author: Aaron Sloman
Title: Applying Systemic Design to the study of `emotion'
Author: Tim Read
Title: Computational Constraints for Associative Learning
Author: Edmund Shing
Title: Explorations in Design Space
Author: Aaron Sloman
Title: Representations as control substates (DRAFT)
Author: Aaron Sloman
Title: Semantics in an intelligent control system
Author: Aaron Sloman
Title: A Summary of the Attention and Affect Project
Author: Ian Wright
Title: Varieties of Formalisms for Knowledge Representation
Author: Aaron Sloman
Title: Systemic Design: A Methodology For Investigating Emotional
Author: Tim Read
Title: The Terminological Pitfalls of Studying Emotion
Authors: Tim Read and Aaron Sloman
Title: Cassandra: Planning with contingencies
Authors: Louise Pryor and Gregg Collins
Title: The Mind as a Control System,
Author: Aaron Sloman
Title: Prospects for AI as the General Science of Intelligence
Author: Aaron Sloman
Title: A study of motive processing and attention,
Authors: Luc P. Beaudoin and Aaron Sloman
Title: What are the phenomena to be explained?
Author: Aaron Sloman
Title: Towards an information processing theory of emotions
Author: Aaron Sloman
Title: Silicon Souls, How to design a functioning mind
Author: Aaron Sloman
Title: The Emperor's Real Mind (Review of Penrose)
Author: Aaron Sloman
Title: Prolegomena to a Theory of Communication and Affect
Author: Aaron Sloman
Title: Notes on consciousness
Author: Aaron Sloman
Title: How to dispose of the free will issue
Author: Aaron Sloman
Title: Motives Mechanisms and Emotions
Author: Aaron Sloman
Title: Reference without causal links,
Author: Aaron Sloman
Title: What enables a machine to understand?
Author: Aaron Sloman
Title: Why we need many knowledge representation formalisms,
Author: A.Sloman
Filename: sloman-on-velmans-bbs.pdf (PDF)
Title: Developing concepts of consciousness
Commentary on 'Is Human Information Processing Conscious',Author: Aaron Sloman
By Max Velmans
in Behavioural and Brain Sciences C.U.P., 1991
Where published:
Behavioral and Brain Sciences, Vol 14, Issue 04, Dec, 1991, pp. 694--695,
http://dx.doi.org/10.1017/S0140525X00072071
Extract:
Velmans cites experiments undermining hypotheses about causal roles for consciousness in perception, learning, decision making, and so on. I'll leave it to experts to challenge the data, as I want to concentrate on removing the surprising sting in the tail of the argument.
.................
Conjecture: This (very difficult) design-based strategy for explaining phenomena that would support talk of consciousness will eventually explain it all. We shall have evidence of success if intelligent machines of the future reject our explanations of how they work, saying it leaves out something terribly important, something that can only be described from the first-machine point of view.
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.
Abstract:
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.Having always admired Popper and been deeply influenced by some of his ideas (even though I do not agree with all of them) I feel privileged at being invited to contribute to a volume of commentaries on his work. My brief is to indicate the relevance of work in Artificial Intelligence (henceforth AI) to Popper's philosophy of mind. Materialist philosophers of mind tend to claim that world2 is reducible to world1. I shall try to show how AI 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 of this paper can be summed up by the slogan: "Any intelligent ghost must contain a computational machine".
Filename: personal-ai-sloman-1988.html (HTML)
Filename: personal-ai-sloman-1988.pdf (PDF)
Title: A Personal View Of Artificial Intelligence
Author: Aaron Sloman
Date Installed: 4 Sep 2012 (First published 1989)
Where published:
Preface to Computers and Thought 1989
By Mike Sharples, David Hogg, Chris Hutchinson, Steve Torrance, and David Young
MIT Press, 20 Oct 1989 - 433 pagesThis preface has also been available since about 1988 as a 'TEACH' file in the Poplog system: TEACH AITHEMES
Abstract:
(Extract from Introduction:)
There are many books, newspaper reports and conferences providing information and making claims about Artificial Intelligence and its lusty baby the field of Expert Systems. Reactions range from one lunatic view that all our intellectual capabilities will be exceeded by computers in a few years time to the slightly more defensible opposite extreme view that computers are merely lumps of machinery that simply do what they are programmed to do and therefore cannot conceivably emulate human thought, creativity or feeling. As an antidote for these extremes, I'll try to sketch a sane middle-of-the-road view.
Towards a Computational Theory of Mind (PDF)
Aaron Sloman
(First published 1984 -- installed here with a new end-note 8 Aug
2012. Details in another file.)
Filename: skills-cogsci-81.pdf
(PDF)
Filename: skills-cogsci-81.txt
(Plain Text)
Filename: skills-cogsci-81.ps
(Postscript)
Title: Skills Learning and Parallelism
In Proceedings Cognitive Science Conference, Berkeley, 1981.
Author: Aaron Sloman
Date Installed: 15 Jan 2008 (Written April 1981)
Abstract:
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.
Abstract:
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: http://www.cs.bham.ac.uk/research/poplog/packages/simagent.html
Abstract:
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.
Emotions are contrasted with attitudes and moods.
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
Abstract:
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.
Filename: sloman.pop11.pdf
Filename: Sloman.pop11.html (HTML
Added 17 Jan 2009
Filename: Sloman.pop11.txt Plain text
Filename: sloman.pop11.ps
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
Abstract:
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 most
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
http://www.cs.bham.ac.uk/research/poplog/poplog.info.html
This paper first appeared in a collection published in 1989 to celebrate the 21st birthday of the Pop family of languages.
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,Date: Originally published 1979. Added here 2 Dec 2000
(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.
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: Sloman.ijcai95.txt (Plain text)
Filename: Sloman.ijcai95.pdf
Filename: Sloman.ijcai95.ps
Authors: Aaron Sloman
Title: A Philosophical Encounter
This is a four page paper, introducing a panel 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.'
Many thanks to Takashi Gomi, at Applied AI Systems Inc, who took the picture.
John McCarthy also contributed a short paper on interactions
between Philosophy and AI, available via his WEB page:
http://www-formal.stanford.edu/jmc/
Date: 24 April 95
Abstract:
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.
Filename: Sloman.scai95.ps
Filename: Sloman.scai95.pdf
Authors: Aaron Sloman
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.
Date: 16 April 1995
Abstract:
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.
Filename: Riccardo.Poli_Mike.Brayshaw.hybrid.system.ps
Filename: Riccardo.Poli_Mike.Brayshaw.hybrid.system.pdf
Title: A Hybrid Trainable Rule-based System
School of Computer Science, the University of Birmingham
Cognitive Science technical report: CSRP-95-4
Date: 31 March 1995
Authors: Riccardo Poli and Mike Brayshaw
Abstract:
In this paper we introduce a new formalism for rule specification that
extends the behaviour of a traditional rule based system and allows the
natural development of hybrid trainable systems.
The formalism in itself allows a simple and concise specification of
rules and lends itself to the introduction of symbolic rule induction
mechanisms (example-based knowledge acquisition) as well as artificial
neural networks.
In the paper we describe such a formalism and four increasingly powerful
mechanisms for rule induction. The first one is based on a truth-table
representation; the second is based on a form of example based learning;
the third on feed-forward artificial neural nets; the fourth on genetic
algorithms.
Examples of systems based on these hybrid paradigms are presented and
their advantages with respect to traditional approaches are discussed.
Filename: sim_agent.pdf
November 1994 Seminar Slides. (PDF)
Filename: sim_agent.ps.gz
November 1994 Seminar Slides. (Gzipped Postscript)
Postscript/PDF version of some seminar slides
presenting the package. Partly out of date.
Filename: simagent.html
http://www.cs.bham.ac.uk/research/projects/poplog/packages/simagent.html
Link to the main SIM_AGENT overview page.
Includes a pointer to some movies demonstrating simple uses of the
toolkit.
Author: Aaron Sloman and Riccardo Poli
Date: November 1994 to March 1995
Abstract:
These files give 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 summarised above,
Aaron.Sloman_Riccardo.Poli_sim_agent_toolkit.ps.gz
Filename: Luc.Beaudoin_thesis.pdf
(PDF)
Filename: Luc.Beaudoin_thesis.ps
(postscript.)
Filename: Luc.Beaudoin_thesis.ps.gz
(Compressed postscript.)
Filename: Luc.Beaudoin_thesis.rtf.gz
(Original rtf format, gzipped.)
Filename: Luc.Beaudoin_thesis.txt.gz
(Plain text version gzipped)
Title: Goal processing in autonomous agents
Date: 31 Aug 1994 (Updated March 13th 1995)
(PDF version added 18 May 2003.)
Author: Luc P. Beaudoin
Abstract:
A thesis submitted to the Faculty of Science of the University of
Birmingham for the degree of PhD in Cognitive Science.
(Supervisor: Aaron Sloman).
Synopsis
The objective of this thesis is to elucidate goal processing in
autonomous agents from a design-stance. A. Sloman's theory of autonomous
agents is taken as a starting point (Sloman, 1987; Sloman, 1992b). An
autonomous agent is one that is capable of using its limited resources
to generate and manage its own sources of motivation. A wide array of
relevant psychological and AI theories are reviewed, including theories
of motivation, emotion, attention, and planning. A technical yet rich
concept of goals as control states is expounded. Processes operating on
goals are presented, including vigilational processes and management
processes. Reasons for limitations on management parallelism are
discussed. A broad design of an autonomous agent that is based on M.
Georgeff's (1986) Procedural Reasoning System is presented. The agent is
meant to operate in a microworld scenario. The strengths and weaknesses
of both the design and the theory behind it are discussed. The thesis
concludes with suggestions for studying both emotion ("perturbance") and
pathologies of attention as consequences of autonomous goal processing.
Filename: Aaron.Sloman_why_robot_emotions.ps
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
Abstract:
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.)
NB
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.
Filename: Ian.Wright_emotional_agent.ps.gz
Filename: Ian.Wright_emotional_agent.ps
Filename: Ian.Wright_emotional_agent.pdf
Title: An Emotional Agent -- The Detection and Control of Emergent
States in an Autonomous Resource-Bounded Agent
(PhD Thesis Proposal)
Date: October 31 1994
Author: Ian Wright
Abstract:
In dynamic and unpredictable domains, such as the real world, agents
are continually faced with new requirements and constraints on the
quality and types of solutions they produce. Any agent design will
always be limited in some way. Such considerations highlight the need
for self-referential mechanisms, i.e. agents with the ability to examine
and reason about their internal processes in order to improve and control
their own functioning.
This work aims to implement a prototype agent architecture that meets
the requirements for self-referential systems, and is able to exhibit
perturbant (`emotional') states, detect such states and attempt to
do something about them. Results from this research will contribute
to autonomous agent design, emotionality, internal perception and
meta-level control; in particular, it is hoped that we will
i. provide a (partial) implementation of Sloman's theory of
perturbances (Sloman, 81) within the NML1 design (Beaudoin, 94),
ii. investigate the requirements for the self-detection and control
of processing states, and
iii. demonstrate the adaptiveness of, the need for, and consequences
of, self-control mechanisms that meet the requirements for
self-referential systems.
Filename: Aaron.Sloman_musings.ps
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),
Diagrammatic Reasoning: Computational and Cognitive
Perspectives,
AAAI Press 1995
Author: Aaron Sloman
Date: 17 October 1994
Abstract:
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
Filename: emotions_workshop95
Title: Geneva Emotion Week 1995
Date: October 1994
Call for Applications
GENEVA EMOTION WEEK '95
April 8 to April 13, 1995
University of Geneva, Switzerland
The Emotion Research Group at the University of Geneva announces the third GENEVA EMOTION WEEK (GEW '95), consisting of a colloquium focusing on a major topic in the psychology of emotion, and of a series of workshops designed to introduce participants to advanced research methods in the field of emotion. In combination with WAUME95.
Filename: Aaron.Sloman_towards.th.rep.ps
Filename: Aaron.Sloman_towards.th.rep.pdf
Title: Towards a general theory of representations
Author: Aaron Sloman
In Donald Peterson (ed)
Forms of representation, Intellect Books, 1996
Date: 31 July 1994
Abstract:
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
Filename: Aaron.Sloman_isre.pdf
Filename: Aaron.Sloman_isre.ps.gz
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)
Authors: Aaron Sloman, Luc Beaudoin and Ian Wright
Revised version in Proceedings ISRE94, edited by Nico Frijda,
ISRE Publications. Email: frijda@uvapsy.psy.uva.nl
Date: 29 July 1994 (PDF version added 25 Dec 2005)
Abstract:
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.
Filename: Tim.Read_Applying_S.D.pdf (PDF)
Filename: Tim.Read_Applying_S.D.ps.gz
Title: Applying Systemic Design to the study of `emotion'
Presented at AICS94, Dublin Ireland
Author: Tim Read
Presented at AICS94, Dublin Ireland
Date: 20th July 1994
Abstract:
Emotion has proved a difficult concept for researchers to explain. This is
principally due to both terminological and methodological problems. Systemic
Design is a methodology which has been developed and used for studying emotion
in an attempt to resolve these difficulties, providing a step toward a
complete understanding of `emotional phenomena'. This paper discusses the
application of this methodology to study the three mammalian behavioural
control systems proposed by Gray (1990). The computer simulation
presented here models a rat in the Kamin (1957) avoidance experiment
for two reasons: firstly, to demonstrate how Gray's systems can form a large
part of the explanation of what is happening in this experiment (which has
proved difficult for researchers to do so far), and secondly, as avoidance
behaviour and its associated architectural concomitance are related to many so
called `emotional states'.
Filename: Ed.Shing_Constraining.Learning.ps.gz
Title: Computational Constraints for Associative Learning
Date: 15 May 1994
Author: Edmund Shing
Abstract:
Due to the dynamic nature of the real world, learning in intelligent
agents requires various processes of selection ("attention to") of
input features in order to facilitate computational tractability.
There are many different forms of learning observed in people and
animals; this research looks at reinforcement learning and analyses
the selection processes necessary for this to work effectively.
Machine learning work has traditionally concentrated on small
predictable domains (the "deep and narrow" approach to cognitive
simulation) and so has avoided the combinatorial explosion problem
faced by an adaptive agent situated in a complex and dynamic world.
A preliminary analysis of several forms of learning suggests that (a)
adaptive agent architectures require selection processes in order to
perform any "useful" learning; and (b) reinforcement learning coupled
with certain simple selection, monitoring and evaluation mechanisms
can achieve several seemingly more complex forms of learning.
An agent design is constructed following a "broad and shallow"
approach to meet both general (e.g. related to fundamental properties of
the real world) and specific (e.g. related to the specific theory
proposed) requirements, concentrating on learning and selection
mechanisms in the implementation of reinforcement learning. This
agent architecture should exhibit both expected reinforcement
learning behaviours and seemingly more complex learning
behaviours. Implications of this work are discussed.
Filename: Aaron.Sloman_explorations.ps
Filename: Aaron.Sloman_explorations.pdf
Title: Explorations in Design Space
Author: Aaron Sloman
Date: 20 April 1994
in Proc
ECAI94, 11th European Conference on Artificial Intelligence
Edited by A.G.Cohn, John Wiley, pp 578-582, 1994
Abstract:
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.
Filename: Aaron.Sloman_representations.control.pdf
Filename: Aaron.Sloman_representations.control.ps
Filename: Aaron.Sloman_representations.control.ps.gz
Title: Representations as control substates (DRAFT)
Author: Aaron Sloman
Date: March 6th 1994
Abstract:
(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
Filename: Aaron.Sloman_semantics.ps
Filename: Aaron.Sloman_semantics.pdf
Title: Semantics in an intelligent control system
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
Author: Aaron Sloman
Date: May 11 1994
Abstract:
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
\ul{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.
Filename: Ian.Wright_Project_Summary.pdf (PDF)
Filename: Ian.Wright_Project_Summary.ps.gz
Title: A Summary of the Attention and Affect Project
Date: March 2nd 1994
Author: Ian Wright
Abstract:
The Attention and Affect project is summarized. The original aims
of the project are reviewed and the work to date described, followed
by a critique of the project in terms of the original aims.
Some ideas for future work are outlined.
Filename: Aaron.Sloman_variety.formalisms.ps
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
Abstract:
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
Filename: Tim.Read_Systemic.Design.pdf (PDF)
Filename: Tim.Read_Systemic.Design.ps.gz
Title: Systemic Design: A Methodology For Investigating Emotional
Phenomena
Presented at WAUME93
Author: Tim Read
Date: August 1993
Abstract:
In this paper I introduce Systemic Design as a methodology for
studying complex phenomena like those commonly referred to as being
emotional. This methodology is an extension of the design-based
approach to include: organismic phylogenetic considerations, a
holistic design strategy, and a consideration of resource limitations.
It provides a powerful technique for generating theoretical models of
the mechanisms underpinning emotional phenomena, the current
terminology associated with which is often muddled and inconsistent.
This approach enables concepts and mechanisms to be clearly specified
and communicated to other researchers in related fields.
Filename: Tim.Read-et.al_TerminlogyPit.pdf
Filename: Tim.Read,et.al_Terminology.Pit.ps.gz
Title: The Terminological Pitfalls of Studying Emotion
Authors: Tim Read and Aaron Sloman
(This paper is written by the first author with ideas developed
from conversations with the second).
Date: Aug 1993
Abstract:
The research community is full of papers with titles that include
terms like `emotion', `motivation', `cognition', and `attention'.
However when these terms are used they are either considered to be so
obvious as not to warrant a definition, or are defined in overly
simplistic and arbitrary ways. The reasons behind our usage of
existing terminology is easy to see, but the problems inherent with it
are not. The use of such terminology gives rise to a whole set of
problems, chief among them are confusion and pointless semantic
disagreement.
These problems occur because the current terminology is too vague, and
burdened with acquired meaning. We need to replace it with terminology
that emerges from a putatively complete theory of the conceptual space
of mechanisms and behaviours, spanning several functional levels
(e.g.: neural, behavioural and computational). Research that attempts
to use the current terminology to build larger and more complex
theory, just adds to the existing confusion.
In this paper I examine the reasons behind the use of current
terminology, explore the problems inherent with it, and offer a way to
resolve these problems. The days when one small research team could
hope to produce a theory to explain the complete range of phenomena
currently referred to as being `emotional' have passed. It is time for
concerted and coordinated activity to understand the relation of
mechanisms to behaviour. This will give rise to clear and unambiguous
terminology that is defined at different functional levels. Until the
current terminological problems are solved, our rate of progress will
be slow.
Filename: Louise.Pryor,et.al_Cassandra.ps.Z
Title: Cassandra: Planning with contingencies
Authors: Louise Pryor and Gregg Collins
Date: Sept 1993
Abstract:
A fundamental assumption made by classical planners is that there is no
uncertainty in the world: the planner has full knowledge of the initial
conditions in which the plan will be executed, and all actions have
fully predictable outcomes. These planners cannot therefore construct
contingency plans that is, plans that specify different actions to be
performed in different circumstances. In this paper we discuss the
issues that arise in the representation and construction of contingency
plans and describe Cassandra, a complete and sound partial-order
contingent planner that uses a single simple mechanism to represent
unknown initial conditions and the uncertain effects of actions.
Cassandra uses explicit decision steps that enable the agent executing
the plan to decide which plan branch to follow. The decision steps in a
plan result in subgoals to acquire knowledge, which are planned for in
the same way as any other subgoals. Unlike previous systems, Cassandra
thus distinguishes the process of gathering information from the
process of making decisions, and can use information-gathering actions
with a full range of preconditions. The simple representation of
uncertainty and the explicit representation of decisions in Cassandra
allow a coherent approach to the problems of contingent planning, and
provide a solid base for extensions such as the use of different
decision making procedures.
Filename: Louise.Pryor,et.al_R.Features.ps.Z
Title: Reference features as guides to reasoning about opportunities
Authors: Louise Pryor and Gregg Collins
Date: Feb 1993
Abstract:
An intelligent agent acting in a complex and unpredictable world must
be able to both plan ahead and act quickly to changes in its
surroundings. In particular, such an agent must be able to react
quickly when faced with unexpected opportunities to fulfill its goals.
We consider the issue of how an agent should respond to perceived
opportunities, and we describe a method for determining quickly
whether it is rational to seize an opportunity or whether a more
detailed analysis is required. Our system uses a set of heuristics
based on reference features to identify situations and objects that
characteristically involve problematic patterns of interaction. We
discuss the recognition of reference features, and their use in
focusing the system reasoning onto potentially adverse interactions
between its ongoing plans and the current opportunity.
Filename: Aaron.Sloman_Mind.as.controlsystem.ps
Filename: Aaron.Sloman_Mind.as.controlsystem.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
Abstract:
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
Filename: Aaron.Sloman_prospects.ps
Filename:
Aaron.Sloman_prospects.pdf
Title: Prospects for AI as the General Science of Intelligence
Author: Aaron Sloman
in Proceedings AISB93, published by IOS Press as a book:
Prospects for Artificial Intelligence
Date: April 1993
Abstract:
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.
Filename: Luc.Beaudoin.and.Sloman_Motive_proc.ps
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.
Authors: Luc P. Beaudoin and Aaron Sloman
Date: April 1993
Abstract:
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.
Filename: Aaron.Sloman_Phenomena.Explain.pdf (PDF)
Filename: Aaron.Sloman_Phenomena.Explain.ps.gz
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
Filename: Aaron.Sloman_IP.Emotion.Theory.pdf (PDF)
Filename: Aaron.Sloman_IP.Emotion.Theory.ps.gz
Title: Towards an information processing theory of emotions
Author: Aaron Sloman
Date: Dec 1992
Seminar notes for the Attention and Affect Project
Filename: Aaron.Sloman_Silicon.Souls.pdf (PDF)
Filename: Aaron.Sloman_Silicon.Souls.ps.gz
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.
Filename: Aaron.Sloman_Emperor.Real.Mind.ps
Filename: Aaron.Sloman_Emperor.Real.Mind.pdf
Filename: sloman_aij_penrose_review.pdf
Title: The Emperor's Real Mind
Author: Aaron Sloman
Lengthy review/discussion of R.Penrose (The Emperor's New
Mind) in the journal Artificial Intelligence
Vol 56 Nos 2-3 August 1992, pages 355-396
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 here.(PDF)
Filename: Aaron.Sloman.et.al_JCI.Grant.ps
Filename: Aaron.Sloman.et.al_JCI.Grant.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.)
WARNING: for some reason the page order of the file is reversed. I'll
fix this one day. (Fixed 15 Feb 2002).
Date: January 1992
Filename: Aaron.Sloman_Prolegomena.ps
Filename: Aaron.Sloman_Prolegomena.pdf
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.
Abstract:
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.
Filename: Aaron.Sloman_consciousness.html (HTML -- added 27 Dec
2007)
Filename: Aaron.Sloman_consciousness.pdf (PDF)
Filename: Aaron.Sloman_consciousness.ps.gz
Title: Notes on consciousness
Author: Aaron Sloman
Abstract:
A discussion on why talking about consciousness is premature
Appeared in AISB Quarterly No 72, pp 8-14, 1990
Filename: Aaron.Sloman_freewill.ps
Filename: Aaron.Sloman_freewill.pdf
Title: How to dispose of the free will issue
Author: Aaron Sloman
Date: 1988 (or earlier)
Originally posted to comp.ai.philosophy circa 1988.
A similar version
appeared in AISB Quarterly, Winter 1992/3, Issue 82,
pp. 31-2.
A plain text version is available online at
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/freewill.disposed.of
(An improved elaborated paraphrase can be found in Chapter 2 of
Stan Franklin
Artificial Minds (MIT Press, 1995).
Paper back version
available.)
Abstract:
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) .
Recently 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.
Filename: Aaron.Sloman_vision.design.pdf (PDF)
(Out of date Postscript version removed. Please use PDF
version instead.)
Filename: Aaron.Sloman_vision.design.html (HTML slightly messy)
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: Original 1989, installed here April 18th 1994
Reformatted, with images included 22 Oct 2006
Footnote at the beginning extended 8 Aug 2012
Abstract:
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.
NOTE:
A precursor to this paper was published in 1982:
Image interpretation: The way ahead?
Some of the author's later work on vision is also on this web site, including
http://www.cs.bham.ac.uk/research/projects/cogaff/talks/#gibson
What's vision for, and how does it work?
From Marr (and earlier) to Gibson and Beyond
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.)
Filename: Sloman.ecai86.ps.gz
Filename: Sloman.ecai86.ps
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.
Date: 1986
Author: Aaron Sloman
Abstract:
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.
Filename: Sloman.ijcai85.ps.gz
Filename: Sloman.ijcai85.ps
Filename: Sloman.ijcai85.pdf
Filename: Sloman.ijcai85.txt
(Plain text original)
Title: What enables a machine to understand?
in
Proceedings 9th International Joint Conference on AI,
pp 995-1001, Los Angeles, August 1985.
Date: 1985
Author: Aaron Sloman
Abstract:
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.
Filename: Aaron.Sloman_Rep.Formalisms.ps.gz
Filename: Aaron.Sloman_Rep.Formalisms.ps
Filename: Aaron.Sloman_Rep.Formalisms.pdf
Author: A.Sloman
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.)
Date: 1985 (Reformatted December 2005)
Abstract:
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
See also the School of Computer Science Web page.
This file, designed to be lynx-friendly, is maintained by
Aaron Sloman.
Email
A.Sloman@cs.bham.ac.uk