From Complexity to Creativity: Explorations in Evolutionary, Autopoietic, and Cognitive Dynamics

392 Pages·1997·4.293 MB·English

by  Ben Goertzel (auth.)

FROM COMPLEXITY TO
CREATIVITY
EXPLORATIONS IN
EVOLUTIONARY, AUTOPOIETIC,
AND COGNITIVE DYNAMICS
International Federation for Systems Research
International Series on Systems Science and Engineering
Series Editor: George .J Klir
State University of New York at Binghamton
Editorial Board
Gerrit Broekstra Ivan M. Havel
Erasmus University, Rotterdam, Charles University, Prague,
The Netherlands Czech Republic
John L. Casti Manfred Pesehel
Santa Fe Institute, New Mexico Academy of Sciences, Berlin, Germany
Brian Gaines Franz Pichler
University of Calgary, Canada University of Linz, Austria
Volume 7 FACETS OF SYSTEMS SCIENCE
George J. Klir
Volume 8 THE ALTERNATIVE MATHEMATICAL MODEL OF
LINGUISTIC SEMANTICS AND PRAGMATICS
Vilrm Nov~ik
Volume 9 CHAOTIC LOGIC: Language, Thought, and Reality from the
Perspective of Complex Systems Science
Ben Goertzel
Volume 10 THE FOUNDATIONS OF FUZZY CONTROL
Harold W. Lewis III
Volume 11 FROM COMPLEXITY TO CREATIVITY: Explorations in
Evolutionary, Autopoietic, and Cognitive Dynamics
Ben Goertzel
IFSR was established "to stimulate all activities associated with the scientific study of systems and to
coordinate such activities at international level." The aim of this series is to stimulate publication of
high-quality monographs and textbooks on various topics of systems science and engineering. This
series complements the Federation's other publications.
.~ Continuation Order Plan is available for this series. A continuation order will bring delivery of each new volume
",mediately upon publication. Volumes are billed only upon actual shipment. For further information please contact
u,e publisher.
Volumes 1-6 were published by Pergamon Press.
FROM COMPLEXITY TO
CREATIVITY
SNOITAROLPXE NI
EVOLUTIONARY, AUTOPOIETIC,
AND COGNITIVE DYNAMICS
NEB LEZTREOG
University of Western Australia
Perth, Western Australia, Australia
PLENUM PRESS • NEW YORK AND LONDON
Llbrary of Congress CataTogtng-lo-Publlcatlon Data
Goertze|. Ben.
From complexity to creativity : explorations in evolutionary,
autopoletlc, dna cognitive dynamics / neB Ooertze.
p. .mc -- (International Federation For Systems Research
lnternattona| series no systems Science dna engineering ; v. )11
Inc|udes bibliographical references dna Index.
NBSI 0-306-45518-8
.1 Cognitive science. 2. Psycho)ogy--Mathematlcal models.
3. Systems theory. I. T|tle. II. Series; IFSR International
series no systems sclence dna engineerlng ; v. .11
475G.~13FB 1997
12cd--351 85935-69
PIC
ISBN 0-306-45518-8
© 1997 Plenum Press, New York
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Printed in the United States of America
A book for thinking --
and nothing besides
HCIRDEI~)F ,EHCZSTEIN
preface to his never-written book,
The Will to Power
Introduction
Cybernetic pioneer Warren McCullough asked: "What is a man, that he
may know a number; and what is a number, that a man may know it?" Thinking
along much the same lines, my question here is: "What is a creative mind, that
it might emerge from a complex system; and what is a complex system, that it
might give rise to a creative mind?"
Complexity science is a fashionable topic these days. My perspective on
complexity, however, is a somewhat unusual one:
I am interested in complex systems science principally as it reflects on
abstract mathematical, computational models of mind. In my three previous
books, The Structure of Intelligence, ehT Evolving Mind, and Chaotic Logic, I
have outlined a comprehensive complex-systems-theoretic theory of mind that
I now call the psynet model.
This book is a continuation of the research program presented in my
previous books (and those books will be frequently referred to here, by the
nicknames ,1$ EM and CL). One might summarize the trajectory of thought
spanning these four books as follows. SI formulated a philosophy and mathemat-
ics of mind, based on theoretical computer science and the concept of "pattern."
EM analyzed the theory of evolution by natural selection in similar terms, and
used this computational theory of evolution to establish the evolutionary nature
of thought. LC deviated much further from the main stream of contemporary
science, and presented the "cognitive equation"--an original mathematical
formalism expressing the structure and dynamics of mind--with applications to
logic, semantics, consciousness, personality, belief systems, and the philosophy
of reality. Now, the present book takes the striking, unorthodox models presented
in ,LC and seeks to draw them back into the fabric of current science, by applying
them to various real-world problems, and connecting them to other theories of
complex system behavior.
The synthetic model of mind presented in ,1$ ,ME and ,LC culminating in
the cognitive equation, is given the name psynet model. The psynet model is
presented in a new and hopefully more clear way, and the connections between
the psynet model and other approaches to complex cognitive systems are drawn
out in detail. The table of contents is broad, voyaging through dynamical
vii
viii Introduction
systems, genetic algorithms, perceptual illusions, fractals, autopoietic systems,
consciousness, time series analysis, dreams, personality theory, the World Wide
Web, and creativity. But even this broad array of topics barely touches the
possible applicability of the psynet perspective. The point is not to say the last
word on any particular topic, but rather to sketch out a general point of view,
which has detailed points to make about every aspect of the mind, and has many
points to make about the more complex aspects of the non-mental world as well.
The diverse interconnections presented here teach us something about the
psynet model, they teach us something about the mental and physical worlds,
and, last but not least, they also teach us something about the other complex
systems models that are discussed. It is very interesting to see how standard
complex systems models must be extended in order to deal with the immense
complexity of the mind. For instance, the theory of polynomial iterations must
be extended to hypercomplex numbers, rather than merely complex numbers.
Genetic algorithms must be extended to incorporate ecology and spatial distri-
bution. Attractor theory must be extended to the study of emergent formal
languages in trajectories. Neural network theories must be made to shift their
emphasis to the structure of interconnection between neuronal groups or mod-
ules.
Some of the explorations presented here are fairly technical; others are
almost entirely nontechnical. Some report concrete scientific research; others are
more speculative. What ties the various chapters together, however, is the focus
on the interface of complexity and mind. The relation of mind and complexity
is a big question, and I certainly do not pretend to have fully resolved it. But I
believe I have made some progress.
In order to guide the reader who may have fairly specific interests, I have
divided the book into four parts. This division is only a rough one, but it serves
to break up the journey from simple mathematical models to subtle human
feelings into comprehensible segments.
Part I, The ComplexMind-Brain, outlines the psynet model and gives some
related ideas that lie fairly close to the model itself--the application of the model
to brain modeling, and the relation of the model to theories of perception. Chapter
2, in particular, gives the conceptual framework for the remainder of the book.
Part II, Formal Tools for Exploring Complexity, is more technical and the
nonmathematical reader might be wisest just to skim it over. It reviews ideas
from dynamical systems theory, genetic algorithms, and abstract algebra, and
shows how these ideas can be extended beyond what is usually done, to provide
tools for thinking about and analyzing the mind. This material provides the
conceptual and scientific inspiration for the ideas in the following Parts.
Part III, Mathematical Structures in the Mind, gives a series of loosely
related applications of the ideas of Parts I and II to various psychological
phenomena: consciousness, dreaming, language production, self-formation, and
even the possibility of intelligence on the World Wide Web.
Introduction ix
Finally, Part IV, ehT scimanyD of Self dna ,ytivitaerC leaves the mathe-
matical precision of Part II even further behind, and attempts to deal with the
stickier problems of personality psychology. What do these complex systems
models tell us about why people act the way they do? The culmination is the final
chapter, which combines personality-psychology ideas with complex-systems
ideas to arrive at a novel, synthetic theory of creativity.
sisponyS
I will now give a more detailed summary of the contents of the individual
chapters.
Chapter One reviews some ideas regarding dynamical systems, genetic
algorithms, and autopoietic systems, which will be useful in following chapters.
Then, Chapter Two reviews the psynet model, the cornerstone of most of
the following chapters. As compared to previous publications, the model is given
a very dynamical twist--it is interpreted to portray the mind as a collection of
interacting, intercreating pattern-recognition and pattern-creation processes, re-
siding on and dynamically creating a "mental graph." Mental entities such as
thoughts, feelings, perceptions and actions are viewed as attractors of spatiotem-
poral pattern/process dynamics. The essence of mental structure is a high-level
emergent meta-attractor called the "dual network," which consists of synergetic
hierarchical and heterarchical structures.
Chapter Three gives a newly detailed psynet-theoretic model of the brain.
Loose connections between the psynet model, the cell assembly theory of
mind/brain, and Neural Darwinism have been made before. Here these general
connections are used to formulate a specific psynet/cortex correspondence, in
which the two aspects of the dual network are mapped onto the two orthogonal
structures of the cortex (pyramidal neurons and cortical layers).
Chapter Four introduces a principle from perceptual psychology, form-en-
hancing distance distortion or "mindspace curvature." This principle emerges
from the study of simple geometric illusions, but it has implications beyond
vision. It is used to solve an outstanding problem within the psynet model as
previously formulated, namely the initial impetus for the formation of the dual
network.
Chapter Five--beginning Part II---turns to pattern--a much-undervalued
concept which is central to the psynet model. It is shown that the theory of
algorithmic pattern allows one to give a complete formalization of complex
systems science, by defining such key terms as system complexity and emer-
gence. Then attention is turned to a new tool for recognizing patterns in dynami-
cal data, the Chaos Language Algorithm or CLA. The CLA, it is argued, indicates
x Introduction
how the psynet model can eventually be put to empirical test. An exploratory
application of the CLA to data on mood fluctuations is reported.
In Chapter Six, the relation between the psynet model and genetic algo-
rithms is elucidated. Some mathematical results about the dynamics of the GA
are summarized, and it is argued that the behavior of the GA with crossover is
more "mind-like" than the behavior of the GA with mutation only. Finally, it is
shown that a spatially distributed genetic algorithm, with ecology included, can
serve as a simple implementation of the psynet model. The genetic algorithm is
viewed as an abstract "ideal form" of certain types of mental creativity.
Chapter Seven is an extended mathematical improvisation on the theme of
"magician systems." Magician systems, collections of entities that collectively
transform and annihilate each other, are central to the rigorous formulation of
the psynet model. However, they have been studied very little, and it is not clear
where they fit in along the spectrum of applied mathematics concepts. Here
magician systems are formulated in terms of directed hypergraphs, and then in
terms ofhypercomplex algebras and yet more abstract, three-operation algebras.
Magician system dynamics (and as a consequence, psynet dynamics) is shown
to have to do with polynomial and rational iterations on these n-dimensional
algebraic spaces.
Chapter Eight, starting off Part III, leaves mathematics behind and turn to
a psychological problem: the question of consciousness. The nature of "raw
consciousness" or raw experience is not entered into; the focus is rather on how
this raw consciousness is elaborated into structured, subjective states of mind.
The first half of the chapter is fairly non-adventurous, and merely expands upon
the concept of the "perceptual-cognitive loop" as introduced in CL. The second
half of the chapter is the most speculative part of the book; it presents a detailed
algebraic theory of states of consciousness, based on the magician system
algebras of Chapter Seven and the quaternionic and octonionic algebras in
particular.
Chapters Nine and Ten apply the psynet model, and complex systems ideas
in general, to two specific psychological problems: the nature of sentence
production, and the purpose of dreams. First, sentence production is viewed as
a process of fractal growth, similar to biological ramification. It is modeled in
terms of L-systems, and evidence for this model is sought in the structure of child
language.
Then, dreaming is considered in the context of the Crick-Mitchison hy-
pothesis, which states that "the purpose of dreams is to forget." Hopfield net
simulations of this hypothesis are considered, and then it is asked: how might
similar phenomena be gotten to arise from the psynet model? The answer leads
one to a theory of dreams that is surprising similar to conventional psychoana-
lytic theories. Dreaming does not simply help one forget, it helps one loosen the
grip of overly dominant autopoietic thought-systems.
Introduction xl
Chapter Eleven turns toward a topic that will preoccupy much of the
remainder of the book: the self. It points out the importance of the psychosocial
self for knowledge representation, and argues that until artificial intelligence
embraces artificial selfhood, it is bound to failure. The emergence of the self
from the dual network is discussed; and the notion of A-IS, or artificial intersub-
jectivity in artificial life worlds, is discussed more thoroughly than in CL.
Elaborating on this train of thought, Chapter Twelve raises the question of
the psychology of the World Wide Web. As the Web becomes more intelligent,
and becomes populated with intelligent agents, might it someday become a
mind? Might it develop self-awareness? The possibility of the Web developing
a magician-system/dual-network structure, as described by the psynet model, is
briefly discussed.
Finally, the last three chapters, constituting Part IV, turn to the difficult and
imprecise, but very rewarding, topic of human personality. Chapter Thirteen
reviews the notion of the dissociated self, and argues that a self is in fact a
multi-part dynamical system. The essence of human personality, it is argued, lies
in the dynamics of various subselves. Martin Buber's distinction between I-You
and I-It interactions is reformulated in terms of emergent pattern recognition,
and it is argued that healthy personalities tend to display I-You interactions
between their various subselves.
In Chapter Fourteen, applications to the theory of romantic love and the
theory of masochism are outlined. These applications are sketchy and sugges-
tive---they are not intended as complete psychoanalytic theories. The point,
however, is to indicate how ideas from complexity science, as represented in the
psynet model, can be seen to manifest themselves in everyday psychological
phenomena. The same dynamics and emergent phenomena that are seen in
simple physical systems, are seen at the other end of the spectrum, in human
thought-feeling-emotion complexes.
Finally, in Chapter Fifteen, the nature of creativity is analyzed, in a way
that incorporates the insights of all the previous chapters. The theory applies to
either human or computer creativity (although, up to this point of history, no
computer program has ever manifested even a moderate degree of creativity, as
compared to the human mind). The existence of a dissociated "creative subself"
in "highly creative people" is posited, and the dynamics of this creative subself
is modeled in terms of the psynet model and the genetic algorithm. The experi-
ence of "divine inspiration" often associated with creativity is understood as a
result of a consciousness-producing "perceptual-cognitive loop" forming part of
a greater emergent pattem. In general, previous complex systems models are
seen as manifestations of particular aspects of the complex creative process.
Creativity, the wellspring of complexity science and all science, is seen to require
all of complexity science, and more, for its elucidation.