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From: AARON SLOMAN Conference: 1252 , comp.ai
To: ALL Message: 252 Reply To: 0
Subj: Re: The concept of inform Date: 06/01/95 Time: 20:44
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ÿ@FROM :A.Sloman@cs.bham.ac.uk N
ÿ@SUBJECT:Re: The concept of information N
ÿ@UMSGID :<3ql8r5$hvc@percy.cs.bham.ac.uk> N
ÿ@UNEWSGR:01comp.ai,comp.ai.philosophy N
From: A.Sloman@cs.bham.ac.uk (Aaron Sloman)
Newsgroups: comp.ai,comp.ai.philosophy
Subject: Re: The concept of information
Date: 1 Jun 1995 20:44:21 GMT
Message-ID: <3ql8r5$hvc@percy.cs.bham.ac.uk>
References:
Xref: uunet comp.ai:30366 comp.ai.philosophy:28701
[I have added comp.ai.philosophy to the Newsgroups line.]
theunissen@psych.kun.nl (Theo Theunissen) writes:
> Date: Tue, 30 May 1995 20:38:36 +0100
> Organization: KUN
>
> In these days of computers, communication is a very intriguing but never
> heard qeustion after the concept of information as a metaphysical
> category.
> We are are very curious if any one else.
I don't know if it's an example of what you are talking about but I
have a paper arguing that there is a (non-syntactic) concept of
information which is used by (for example) software engineers, and
is more fundamental than Newell's "Knowledge Level" or Dennett's
"Intentional Stance".
This concept of information is not essentially connected with
communication between agents, as it can be applied to processes that
occur within an agent (i.e. internal mechanisms acquire, store,
manipulate and use information without necessarily involving
communication with other agents -- but you could call it
"self-communication". However some information essentially involves
external objects, e.g. reference to the Eiffel Tower cannot be based
entirely on the states of internal information processing
mechanisms).
I claim that the information level (which is close to Dennett's
"Design Stance", and is very familiar to engineers even if they do
not normally discuss its metaphysical significance!) provides a
basis on which to consider architectures within which mental
concepts can be defined. I.e. mental states, processes,
capabilities, can be defined in terms of states and processes that
information processing architectures can generate.
So, mental concepts (analogous to "belief", "desire", etc.) are
based on the design stance, not the intentional stance nor Newell's
knowledge level.
The phenomena that occur at the information level are implemented in
physical processes, but are emergent in the sense that:
a. the concepts required for describing them are not definable
in terms of concepts of physics;
b. the laws governing the virtual machines that operate at the
information level are not derivable from laws of physics. E.g.
the information processing rules can be changed without changing
the laws of physics (but not without changing the implementation
in some way);
c. there need not be any simple (let alone one to one)
correlations between events at the information processing level
and physical events, or between structures at the two levels;
d. any particular information level system may be implemented in
very different physical machines (this is similar to point (c)).
My ideas on this are still only vague, intuitive and incomplete and
I welcome suggestions for correction and improvement.
One example of the difference between the information processing
level and the intentional or knowledge level described by Dennett
and Newell is that the information processing level does not depend
on any presumption of rationality. This is important, because I
don't think intelligence in a resource-bounded agent requires
rationality. In fact the requirement for total rationality leads to
all sorts of contradictions and paradoxes that have bedevilled
philosophical discussions of the nature of mind and knowledge for
centuries.
The paper attempting to develop these ideas is:
A.Sloman, Semantics in an intelligent control system,
in
Philosophical Transactions of the Royal Society: Physical
Sciences and Engineering
Vol 349, 1689, pp 43-58 1994
It's available as compressed postscript via ftp or WWW in the
directories
ftp://ftp.cs.bham.ac.uk/pub/dist/cog_affect/
http://www.cs.bham.ac.uk/~axs/cog_affect
in the file called Aaron.Sloman_semantics.ps.Z
There's another paper extending some of the ideas, in the file
Sloman.turing90.ps.Z
(revised version of paper presented at the Turing90 colloquium,
April 1990).
Other papers in the same directory are all part of the same
research programme, including work on motivation and emotions,
and varieties of forms of representation.
Aaron
---
--
Aaron Sloman, ( http://www.cs.bham.ac.uk/~axs )
School of Computer Science, The University of Birmingham, B15 2TT, England
EMAIL A.Sloman@cs.bham.ac.uk OR A.Sloman@bham.ac.uk
Phone: +44-(0)121-414-4775 Fax: +44-(0)121-414-4281
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From: PETER VAN ROY Conference: 1298 , +p.constraints
To: ALL Message: 16 Reply To: 0
Subj: The Grand Challenge Date: 06/01/95 Time: 14:09
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ÿ@FROM :vanroy@dfki.uni-sb.de N
ÿ@ORIGIN :world N
ÿ@UMSGID :<3qkhmj$e5s@hitchcock.dfki.uni-sb.de> N
ÿ@UNEWSGR:01comp.lang.prolog,comp.lang.functional,comp.constraints,comN
ÿ@UNEWSGR:02p.object.logic N
From: vanroy@dfki.uni-sb.de (Peter Van Roy)
Newsgroups: comp.lang.prolog,comp.lang.functional,comp.constraints,comp.object.
logic
Subject: The Grand Challenge
Date: 1 Jun 1995 14:09:23 GMT
Message-ID: <3qkhmj$e5s@hitchcock.dfki.uni-sb.de>
Xref: uunet comp.lang.prolog:13070 comp.lang.functional:6045 comp.constraints:6
88 comp.object.logic:463
The Grand Challenge in Programming Languages
--------------------------------------------
The Grand Challenge in programming languages is to build a *single* simple and
practical system with *maximum* expressiveness. There is *no* system that
provides such useful notions as concurrency, constraints, full compositionality
,
lexical scoping, search, typing, distribution and persistence, while remaining
*simple*. Is this Grand Challenge ludicrous? Well, no. Major progress has
been made. But there is still much to do.
In logic programming, the concurrent constraint programming (CCP) community is
tackling this problem head on and making amazing progress. We use the scientif
ic
method: isolate concepts one by one, reduce them to their essentials, and
incorporate them. We exploit the power of formal models hand-in-hand with the
experience of using practical systems.
The CCP community is having major successes. For example: The AKL project at
SICS was the first to integrate the problem-solving power of constraint logic
programming into a concurrent and reactive language, thus solving a central
outstanding problem of the Japanese Fifth Generation Project. Another
example: The Oz project at the DFKI has first developed a fully-compositional
generalization of CCP that gives first-class status to procedures, objects,
and modules.
The CCP community is world-wide and growing. The developers of the languages
AKL (SICS, Sweden), Oz (DFKI, Germany) and LIFE (PRL, France and SFU, Canada)
have collaborated closely over the last three years in the Esprit project
ACCLAIM. The AKL and Oz projects are converging. LIFE technology is being
integrated into Oz. CCP work is going on in many other places including
Xerox PARC. The ToonTalk system, a successor to Logo, has CCP at its heart.
The DFKI Oz system, released in January 1995, has struck a chord. An
international Oz workshop WOz'95 is independently being organized in
Switzerland. Various projects world-wide are using Oz as their main platform.
The vision of Concurrent Constraint Programming is there and it is gaining
momentum!
Peter
--
-------------------------------------------------------------------------
Peter Van Roy
Programming Systems Lab Tel: +49-681-302-5332
DFKI Fax: +49-681-302-5341
Stuhlsatzenhausweg 3 Net: vanroy@dfki.uni-sb.de
D-66123 Saarbruecken, Germany Web: http://ps-www.dfki.uni-sb.de/~vanroy
-------------------------------------------------------------------------
Contact addresses for Oz are:
oz@dfki.uni-sb.de Bug reports and questions
oz-users@dfki.uni-sb.de To all Oz users
oz-users-request@dfki.uni-sb.de Maintenance of the users list
-------------------------------------------------------------------------
Vacation planning is a problem of mathematical logic. I want to go to
A AND B AND C, but my budget only allows me to go to A OR B OR C. -- K.
-------------------------------------------------------------------------
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fr======================================================================
From: MHB0 Conference: 1252 , comp.ai
To: ALL Message: 258 Reply To: 0
Subj: New Book Announcement Date: 06/01/95 Time: 13:32
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ÿ@FROM :mhb0@Lehigh.EDU N
ÿ@UMSGID :<3qktir$1g0g@ns2-1.CC.Lehigh.EDU> N
ÿ@UNEWSGR:01comp.ai N
From: mhb0@Lehigh.EDU
Newsgroups: comp.ai
Subject: New Book Announcement
Date: 1 Jun 1995 13:32:11 -0400
Message-ID: <3qktir$1g0g@ns2-1.CC.Lehigh.EDU>
Xref: uunet comp.ai:30372
BOOK ANNOUNCEMENT
Foundational Issues in Artificial Intelligence and Cognitive Science:
Impasse and Solution.
Elsevier Science
1995
Mark H. Bickhard
Lehigh University
mhb0@lehigh.edu
Loren Terveen
AT&T Bell Laboratories
terveen@research.att.com
SHORT DESCRIPTION
The book focuses on a conceptual flaw in contemporary artificial
intelligence and cognitive science. Many people have discovered
diverse manifestations and facets of this flaw, but the central
conceptual impasse is at best only partially perceived. Its
consequences, nevertheless, visit themselves as distortions
and failures of multiple research projects - and make impossible
the ultimate aspirations of the fields.
The impasse concerns a presupposition concerning the nature of
representation - that all representation has the nature of encodings:
encodingism. Encodings certainly exist, but encoding*ism* is at root
logically incoherent; any *programmatic* research predicated on it
is doomed to distortion and ultimate failure.
The impasse and its consequences - and steps away from that impasse -
are explored in a large number of projects and approaches. These
include SOAR, CYC, PDP, situated cognition, subsumption architecture
robotics, and the frame problems - a general survey of the current
research in AI and Cognitive Science emerges.
Interactivism, an alternative model of representation, is proposed and
examined.
SYNOPSIS
The central point of Foundational Issues in Artificial Intelligence and
Cognitive Science - Impasse and Solution is that there is a conceptual
flaw in contemporary approaches to artificial intelligence and
cognitive science, a flaw that makes impossible the ultimate
aspirations of these fields. Many people have discovered diverse
manifestations and facets of this flaw, but the central conceptual
impasse is only partially perceived. The consequences, nevertheless,
visit themselves as distortions and failures of research projects
across the fields.
The locus of the impasse concerns a common assumption or
presupposition that underlies all parts of the field - a presupposition
concerning the nature of representation. We call this assumption
"encodingism", the assumption that representation is fundamentally
constituted as encodings. This assumption, in fact, has been
dominant throughout Western history. We argue that it is at root
logically incoherent, and, therefore, that any programmatic research
predicated on it is doomed to distortion and ultimate failure.
On the other hand, encodings clearly do exist, and therefore are
clearly possible, and we show how that could be - but they cannot be
the foundational form of representation. Similarly, contemporary
encoding approaches are enormously powerful, and major advances have
been made within these dominant programmatic frameworks - but the
encodingism flaw in those frameworks limit their ultimate possibilities,
and will frustrate efforts toward the programmatic goal of understanding
and constructing minds.
The book characterizes and demonstrates this impasse, discusses a
number of partial recognitions of and movements away from it, and then
traces its consequences in a large number of projects and approaches
within the fields. These include SOAR, CYC, PDP, situated cognition,
subsumption architecture robotics, and the frame problems. In surveying
the consequences of the impasse, we also provide a general survey of
the current research in AI and Cognitive Science per se.
We do not propose an unsolvable impasse, and, in fact, present an
alternative that does resolve that impasse. This is developed for
contrast, for perspective, to demonstrate that there is an alternative,
and to explore some of its nature. We end with an exploration of
some of the architectural implications of the alternative - called
interactivism - and argue that such architectures are 1) not subject to
the encodingism incoherence 2) more powerful than Turing
machines, 3) more consistent with properties of central nervous
system functioning than other contemporary approaches, and 4)
capable of resolving the many problematics in the field that we argue
are in fact manifestations of the underlying impasse.
The audience for this book will include researchers, academics, and
students in artificial intelligence, cognitive science, robotics, cognitive
psychology, philosophy of mind and language, natural language
processing, connectionism, and learning. The focus of the book is on
the nature of representation, and representation permeates
everywhere - so also, therefore, do the implications of our critique and
our alternative permeate everywhere.
CONTENTS
Preface xi
Introduction 1
A PREVIEW 2
I GENERAL CRITIQUE 5
1 Programmatic Arguments 7
CRITIQUES AND QUALIFICATIONS 8
DIAGNOSES AND SOLUTIONS 8
IN-PRINCIPLE ARGUMENTS 9
2 The Problem of Representation 11
ENCODINGISM 11
Circularity 12
Incoherence - The Fundamental Flaw 13
A First Rejoinder 15
The Necessity of an Interpreter 17
3 Consequences of Encodingism 19
LOGICAL CONSEQUENCES 19
Skepticism 19
Idealism 20
Circular Microgenesis 20
Incoherence Again 20
Emergence 21
4 Responses to the Problems of Encodings 25
FALSE SOLUTIONS 25
Innatism 25
Methodological Solipsism 26
Direct Reference 27
External Observer Semantics 27
Internal Observer Semantics 28
Observer Idealism 29
Simulation Observer Idealism 30
SEDUCTIONS 31
Transduction 31
Correspondence as Encoding:
Confusing Factual and Epistemic Correspondence 32
5 Current Criticisms of AI and Cognitive Science 35
AN APORIA 35
Empty Symbols 35
ENCOUNTERS WITH THE ISSUES 36
Searle 36
Gibson 40
Piaget 40
Maturana and Varela 42
Dreyfus 42
Hermeneutics 44
6 General Consequences of the Encodingism Impasse 47
REPRESENTATION 47
LEARNING 47
THE MENTAL 51
WHY ENCODINGISM? 51
II INTERACTIVISM:
AN ALTERNATIVE TO ENCODINGISM 53
7 The Interactive Model 55
BASIC EPISTEMOLOGY 56
Representation as Function 56
Epistemic Contact: Interactive Differentiation and Implicit Definition 60
Representational Content 61
EVOLUTIONARY FOUNDATIONS 65
SOME COGNITIVE PHENOMENA 66
Perception 66
Learning 69
Language 71
8 Implications for Foundational Mathematics 75
TARSKI 75
Encodings for Variables and Quantifiers 75
Tarski's Theorems and the Encodingism Incoherence 76
Representational Systems Adequate to Their Own Semantics 77
Observer Semantics 78
Truth as a Counterexample to Encodingism 79
TURING 80
Semantics for the Turing Machine Tape 81
Sequence, But Not Timing 81
Is Timing Relevant to Cognition? 83
Transcending Turing Machines 84
III ENCODINGISM:
ASSUMPTIONS AND CONSEQUENCES 87
9 Representation: Issues within Encodingism 89
EXPLICIT ENCODINGISM IN THEORY AND PRACTICE 90
Physical Symbol Systems 90
The Problem Space Hypothesis 98
SOAR 100
PROLIFERATION OF BASIC ENCODINGS 106
CYC - Lenat's Encyclopedia Project 107
TRUTH-VALUED VERSUS NON-TRUTH-VALUED 118
Procedural vs Declarative Representation 119
PROCEDURAL SEMANTICS 120
Still Just Input Correspondences 121
SITUATED AUTOMATA THEORY 123
NON-COGNITIVE FUNCTIONAL ANALYSIS 126
The Observer Perspective Again 128
BRIAN SMITH 130
Correspondence 131
Participation 131
No Interaction 132
Correspondence is the Wrong Category 133
ADRIAN CUSSINS 134
INTERNAL TROUBLES 136
Too Many Correspondences 137
Disjunctions 138
Wide and Narrow 140
Red Herrings 142
10 Representation: Issues about Encodingism 145
SOME EXPLORATIONS OF THE LITERATURE 145
Stevan Harnad 145
Radu Bogdan 164
Bill Clancey 169
A General Note on Situated Cognition 174
Rodney Brooks: Anti-Representationalist Robotics 175
Agre and Chapman 178
Benny Shanon 185
Pragmatism 191
Kuipers' Critters 195
Dynamic Systems Approaches 199
A DIAGNOSIS OF THE FRAME PROBLEMS 214
Some Interactivism-Encodingism Differences 215
Implicit versus Explicit Classes of Input Strings 217
Practical Implicitness: History and Context 220
Practical Implicitness: Differentiation and Apperception 221
Practical Implicitness: Apperceptive Context Sensitivities 222
A Counterargument: The Power of Logic 223
Incoherence: Still another corollary 229
Counterfactual Frame Problems 230
The Intra-object Frame Problem 232
11 Language 235
INTERACTIVIST VIEW OF COMMUNICATION 237
THEMES EMERGING FROM AI RESEARCH IN LANGUAGE 239
Awareness of the Context-dependency of Language 240
Awareness of the Relational Distributivity of Meaning 240
Awareness of Process in Meaning 242
Toward a Goal-directed, Social Conception of Language 247
Awareness of Goal-directedness of Language 248
Awareness of Social, Interactive Nature of Language 252
Conclusions 259
12 Learning 261
RESTRICTION TO A COMBINATORIC SPACE OF ENCODING 261
LEARNING FORCES INTERACTIVISM 262
Passive Systems 262
Skepticism, Disjunction, and the Necessity of Error for Learning 266
Interactive Internal Error Conditions 267
What Could be in Error? 270
Error as Failure of Interactive Functional Indications -
of Interactive Implicit Predications 270
Learning Forces Interactivism 271
Learning and Interactivism 272
COMPUTATIONAL LEARNING THEORY 273
INDUCTION 274
GENETIC AI 275
Overview 276
Convergences 278
Differences 278
Constructivism 281
13 Connectionism 283
OVERVIEW 283
STRENGTHS 286
WEAKNESSES 289
ENCODINGISM 292
CRITIQUING CONNECTIONISM AND
AI LANGUAGE APPROACHES 296
IV SOME NOVEL ARCHITECTURES 299
14 Interactivism and Connectionism 301
INTERACTIVISM AS AN INTEGRATING PERSPECTIVE 301
Hybrid Insufficiency 303
SOME INTERACTIVIST EXTENSIONS OF ARCHITECTURE 304
Distributivity 304
Metanets 307
15 Foundations of an Interactivist Architecture 309
THE CENTRAL NERVOUS SYSTEM 310
Oscillations and Modulations 310
Chemical Processing and Communication 311
Modulatory "Computations" 312
The Irrelevance of Standard Architectures 313
A Summary of the Argument 314
PROPERTIES AND POTENTIALITIES 317
Oscillatory Dynamic Spaces 317
Binding 318
Dynamic Trajectories 320
"Formal" Processes Recovered 322
Differentiators In An Oscillatory Dynamics 322
An Alternative Mathematics 323
The Interactive Alternative 323
V CONCLUSIONS 325
16 Transcending the Impasse 327
FAILURES OF ENCODINGISM 327
INTERACTIVISM 329
SOLUTIONS AND RESOURCES 330
TRANSCENDING THE IMPASSE 331
References 333
Index 367
PREFACE
Artificial Intelligence and Cognitive Science are at a foundational
impasse which is at best only partially recognized. This impasse has
to do with assumptions concerning the nature of representation:
standard approaches to representation are at root circular and
incoherent. In particular, Artificial Intelligence research and Cognitive
Science are conceptualized within a framework that assumes that
cognitive processes can be modeled in terms of manipulations of
encoded symbols. Furthermore, the more recent developments of
connectionism and Parallel Distributed Processing, even though the
issue of manipulation is contentious, share the basic assumption
concerning the encoding nature of representation. In all varieties of
these approaches, representation is construed as some form of
encoding correspondence. The presupposition that representation is
constituted as encodings, while innocuous for *some applied*
Artificial Intelligence research, is fatal for the further reaching
programmatic aspirations of both Artificial Intelligence and Cognitive
Science.
First, this encodingist assumption constitutes a *presupposition*
about a basic aspect of mental phenomena - representation - rather
than constituting a *model* of that phenomenon. Aspirations of
Artificial Intelligence and Cognitive Science to provide any
foundational account of representation are thus doomed to circularity:
the encodingist approach presupposes what it purports to be
(programmatically) able to explain. Second, the encoding
assumption is not only itself in need of explication and modeling, but,
even more critically, the standard presupposition that representation
is *essentially* constituted as encodings is logically fatally flawed.
This flaw yields numerous subsidiary consequences, both conceptual
and applied.
This book began as an article attempting to lay out this basic critique
at the programmatic level. Terveen suggested that it would be more
powerful to supplement the general critique with explorations of
actual projects and positions in the fields, showing how the
foundational flaws visit themselves upon the efforts of researchers.
We began that task, and, among other things, discovered that there is
no natural closure to it - there are always more positions that could be
considered, and they increase in number exponentially with time.
There is no intent and no need, however, for our survey to be
exhaustive. It is primarily illustrative and demonstrative of the
problems that emerge from the underlying programmatic flaw. Our
selections of what to include in the survey have had roughly three
criteria. We favored: 1) major and well known work, 2) positions that
illustrate interesting deleterious consequences of the encodingism
framework, and 3) positions that illustrate the existence and power of
moves in the direction of the alternative framework that we propose.
We have ended up, *en passant*, with a representative survey of
much of the field. Nevertheless, there remain many more positions
and research projects that we would like to have been able to
address.
MAIN FEATURES
Identifies a fundamental premise about the nature of representation
that underlies much of Cognitive Science - that representation is
constituted as encodings.
Explores fatal flaws with this premise.
Surveys major projects within Cognitive Science and Artificial
Intelligence.
Shows how they embody the encodingism premise, and how they are
limited by it.
Identifies movements within Cognitive Science and AI away from
encodingism.
Presents an alternative to encodingism - interactivism.
Demonstrates that interactivism avoids the fatal flaws of
encodingisms, and that it provides a coherent framework for
understanding representation.
Unifies insights from the various movements in Cognitive Science
away from encodingism.
Sketches an interactivist cognitive architecture.
FIELDS OF INTEREST
Cognitive Science
Simulation of Cognitive Processes
Artificial Intelligence, Knowledge Engineering, Expert Systems
Human Information Processing
Philosophy of Language
Philosophy of Mind
Cognitive Psychology
Robotics
Artificial Life
Autonomous Agents
Dynamic Systems and Behavior
Learning
Theory of Computation
Semantics
Pragmatics
Connectionism
Linguistics
Neuroscience
Bickhard, M. H., Terveen, L. (1995). Foundational Issues in Artificial
Intelligence and Cognitive Science - Impasse and Solution. Elsevier
Scientific.
ISBN 0 444 82048 5
In the US/Canada orders may be placed with:
Elsevier Science
P.O. Box 945
New York, NY 10159-0945
Phone (212) 633-3750
Fax (212) 633-3764
Email: usorders-f@elsevier.com
Elsevier has given this book an unfortunately high price: Dfl. 240 --
US$ 141.25. We deeply regret that. Nevertheless, we suggest that
it is well worth taking a look at, whether by purchase, local library,
or inter-library loan.
Mark H. Bickhard
Department of Psychology
17 Memorial Drive East
Lehigh University
Bethlehem, PA 18015
610-758-3633