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
@FROM   :A.Sloman@cs.bham.ac.uk                                      N
@SUBJECT:Re: The concept of information                              N
@UMSGID :<3ql8r5$hvc@percy.cs.bham.ac.uk>                            N
@UNEWSGR:01comp.ai,comp.ai.philosophy                                N
From: A.Sloman@cs.bham.ac.uk (Aaron Sloman)
Newsgroups: comp.ai,comp.ai.philosophy
Subject: Re: The concept of information
Date: 1 Jun 1995 20:44:21 GMT
Message-ID: <3ql8r5$hvc@percy.cs.bham.ac.uk>
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

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

The paper attempting to develop these ideas is:

    A.Sloman, Semantics in an intelligent control system,
    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


in the file called Aaron.Sloman_semantics.ps.Z

There's another paper extending some of the ideas, in the file


(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 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
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
@FROM   :vanroy@dfki.uni-sb.de                                       N
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@UMSGID :<3qkhmj$e5s@hitchcock.dfki.uni-sb.de>                       N
@UNEWSGR:02p.object.logic                                            N
From: vanroy@dfki.uni-sb.de (Peter Van Roy)
Newsgroups: comp.lang.prolog,comp.lang.functional,comp.constraints,comp.object.
Subject: The Grand Challenge
Date: 1 Jun 1995 14:09:23 GMT
Message-ID: <3qkhmj$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
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



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.

From: MHB0                      Conference: 1252 , comp.ai
  To: ALL                       Message: 258  Reply To: 0
Subj: New Book Announcement     Date: 06/01/95  Time: 13:32
@FROM   :mhb0@Lehigh.EDU                                             N
@UMSGID :<3qktir$1g0g@ns2-1.CC.Lehigh.EDU>                           N
@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


Foundational Issues in Artificial Intelligence and Cognitive Science:
Impasse and Solution.

Elsevier Science

Mark H. Bickhard
Lehigh University

Loren Terveen
AT&T Bell Laboratories


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


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.


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

     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

     ASSUMPTIONS AND CONSEQUENCES                                       87

9  Representation:  Issues within Encodingism                           89

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

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


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
     AI LANGUAGE APPROACHES                                             296

IV  SOME NOVEL ARCHITECTURES                                            299

14  Interactivism and Connectionism                                     301

Hybrid Insufficiency                                                    303

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


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

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


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

Shows how they embody the encodingism premise, and how they are
limited by it.

Identifies movements within Cognitive Science and AI away from

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.


        Cognitive Science
        Simulation of Cognitive Processes
        Artificial Intelligence, Knowledge Engineering, Expert Systems
        Human Information Processing
        Philosophy of Language
        Philosophy of Mind
        Cognitive Psychology
        Artificial Life
        Autonomous Agents
        Dynamic Systems and Behavior
        Theory of Computation

Bickhard, M. H., Terveen, L.  (1995).  Foundational Issues in Artificial
Intelligence and Cognitive Science - Impasse and Solution.  Elsevier

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