Self-Organizing Natural Intelligence Book

Introduction     xvii
List of Abbreviations     xxvii
List of Figures and Tables     xxix
Acknowledgements     xxxi
The Problem of Intelligence     1
Some of the Basic Issues     4
The Single and Multiple Capacity Views     5
Where Are the Facts of Intelligence Found?     6
The Faulty Sciences of Intelligence     7
The Anti-Theory Bias     8
A Misleading Heritage of Inductivism     8
Confusing Cause and Correlation     9
Invalid Reductionism     10
The Faulty Genetic Argument     11
A Neo-Darwinist Influence     12
Neglect of Emerging Intelligence     14
Inadequacies of the Classical Linear Approach     15
Neglect of Theory Construction and Concept Formation     16
Mechanism and Organicism     17
Narrowing the Intelligence Domain to Suit Tools At Hand     21
Unexamined Assumptions, Concepts, and Fallacies     21
The Scope of Cognition     22
A Bankrupt Theory of Knowing in the Sciences of Intelligence     25
Kinds of Knowing and the Intellectualist Legend     26
A Missing Distinction between Rule-governed and Rule-boundIntelligence     27
Neglect of Multiple Signs and Disclosure of Intelligence     29
Signals, Cues, and Clues     29
Exhibiting and Disclosing Intelligence     30
Mechanical "Hard-Wired" and Natural Intelligence: Absent the Difference     32
Requirements for a New Science of Intelligence     33
A Broader Theory of Knowing     34
Knowledge That, Knowing How, Immediate Awareness     34
A Broader Theory of Signs of Intelligence     37
Toward Three-Dimensional Signs and Patterns     38
Methods of Nonlinear Science: The Emergence of Self-Organizing Dynamical Intelligence     40
Self-Organization     40
Theory Models Approach to Intelligence Inquiry     42
Set Theory     42
Information Theory     43
Graph Theory and Dynamical Systems Theory     43
From a Symbol-based View to a Geometric View of Natural Intelligence     44
Summary     45
The Universe of Intelligence     49
Carving the Problem Space     49
Rational Inquiry and Ideology: The Differences     50
Careless Carving     52
Classical Origins and Fabric of Intelligence Theory: Cut on Biases     53
Plato and Aristotle's Conflicting Theoretical Stage     54
Plato's Dichotomy of Mind and Body     55
Aristotelian Dictum: Anatomy and Intelligence are Destiny     56
Early Differences Between Theory and Practice     57
Anthropocentrism, Language, Gender, Race, Size, Wealth, and Place     58
The Intrinsic and Instrumental Intelligence Difference     59
The Intelligence Center of the Universe     59
The Fabric of Concepts Defining Intelligence Since Darwin     60
Reason, Logic and Language     62
Number     63
Knowledge     64
The Continuing Cartesian "Split": Body and Mind     65
Making the Natural Artificial     69
The Intelligence of the Large and Small     70
Brainless Intelligence and Intentionality?     71
Today's IQ Tests: Circularity, Bias, and American Eugenics     73
The Economic Argument     74
The Issue of Test Validity     75
Reification and the Eugenics Argument     76
A Static Hierarchy: g the Controller     78
Missing From g: Experience     80
Biological Determinism Revisited     83
Neo-Darwinism and the Heritability Argument     83
A Short History of Rising IQ Scores     87
Suspect Racial Sorting     89
Summary     90
The Genesis of Intelligence: Innate and Emergence Arguments     93
Categorization, Classification, Concepts and Representation     93
Reality and the Influence of Representationalism     95
The Continuing Problem with Universals (Concepts): Some History     96
Plato     96
Aristotle     99
Realists, Conceptualists, and Nominalists on Universals     101
Theories of Knowledge and the Scope of Intelligence     102
Realism, Coherence, and Pragmatism     103
The Language Interface Issue     105
A Postmodern Heritage and Realist Counterargument     108
Today's Representationalist Myths: Cognitive Maps in the Brain     110
The Innate Versus Emergence Arguments     113
The Genetically Encoded Syntax Argument     113
Nonverbal Communication: Beyond Alphanumeric Symbols and Vocalizations     115
Gestures     116
From Manual Gestures to Whole Body Performances     118
Evolutionary Argument against Innatists     120
Cognitivism, Mechanism, and "Innateness": How the Mind Does Not Work     122
Innate Learning Mechanisms      123
The Classical Computational View of Mind and Intelligence     124
Missing Practical Intelligence     125
Rationalist Sources of Innate Arguments     126
Summary     128
The Intelligence of Doing: Sensorimotor Domains and Knowing How     131
The Intelligence of Doing     131
A Two-Pronged Approach to Intelligence Inquiry     133
Fallacies to Avoid     134
Cognition, Consciousness, Awareness     136
The Science of Awareness     138
Cortical Structures and Information: Neural Bases of Awareness and Intelligent Doing     140
Reticulo-Thalamo-Cortical (RTC) System     143
How Concepts (Universals) Get Formed: A Global Map Theory     143
The Bogus Process of Abstraction     145
A Spurious Sense of Induction: The Appeal to "Sampling"     146
A Problem with Attention     147
Primitive Awareness     147
Scientific Definitions of "Awareness"     148
Possible Subject Bias     149
Awareness of and Awareness that     150
Experimental Evidence of Immediate Awareness     150
Evidence of Awareness Under Anesthesia     154
What the Experiments Show     156
Primitives of the Preattentive Phase of Awareness     157
Visual Fields     158
Preattentive and Automatic Processes     160
Primitive Preattentive Features, Processes and Cognition     161
Preattentive Feature Integration     164
Possible Dichotomy of Visual Discrimination     165
Detection and Attention to Faces     166
Primitive Intelligence of Moving and Touching     167
Multiple Spaces of the Senses, Images and Probing     168
Smoothness and Timing in Intelligent Doing     173
Limitations of Computational Models of Awareness: Selection without Classification     174
Summary     176
Where We Enter the Circle of Cognition: Immediate Awareness     176
Primitive Selection and Problems with Consciousness     178
Universals, Mathematical Thought and Awareness     181
On the Origins and Nature of Mathematical Thought     182
The Genetic Fallacy     183
A Postmodern View: The Body Shapes Development and Content of Mathematics     184
Conceptual Metaphors and Begging the Question     187
The Language Causal Argument: Language Shapes the Development and Content of Mathematics     188
The Neurological Evidence     190
Thinking in Patterns and Images     192
Mathematical Thought and Space     193
Space and Theorem-Proving     194
The Realism Argument: Reality and Reason Shape the Development and Content of Mathematics     196
Ontological and Epistemological Issues     197
Structure of Our Inquiry     198
Platonic and Hilbertian Mathematics: The Issues     199
The Second Theorem     200
The Non-algorithmic Nature of Mathematical Insight     202
Implications of Non-algorithmic Insight to a Science of Intelligence     203
Other Mathematical Sources of Non-algorithmic Intelligence     203
Problems with Representation Theories Revisited     204
Naming, Indexes, Classification, Sets, Kinds and Types     205
Classification and the Nature of Sui Generis Objects of Immediate Awareness     208
Phenomenal Experience and Mathematics     209
Demonstrating the Problem with Indexicals     211
Retroduction, Reality and Non-algorithmic Insight     212
Perception and Mathematical Objects     213
The Reality of Sets and Concepts     215
Intersubjective Requirements of Mathematical Thought     218
Summary     219
Intelligence as Self-Organizing Emerging Complexity      223
Categories of Natural Intelligence     223
Self-Organization and Pattern Formation     224
Emergence     226
Interactive Systems and Self-Organization     227
Complexity     228
Mechanism and Organicism Revisited     230
Organized Simplicity and Unorganized Complexity     230
Organized Complexity     232
Causality     234
Nonlinear Theory Models Approach to Natural Intelligence     235
The SIGGS Theory Model     238
Information Theory     240
Information-Theoretic Extensions of Simple Feedback Model     242
SIGGS Applied to Natural Intelligence Systems     244
Elements and Signs of Natural Intelligence     244
The Use of Digraph Theory to Characterize Intelligence Relations     246
Social Network Theory and Patterns of Intelligence     249
Fundamental Properties of Networks: Density and Connectedness     251
Partial Order on the Intelligence Set     253
Information-Theoretic Measures on Natural Intelligence Systems     255
Information-Theoretic (Uncertainty) Measures of Intelligence     256
Measures of Uncertainty and Intelligence Categories of Occurrences      257
Information-Theoretic Measures of the Universal Intelligence Set     259
From a Symbol-based View to a Geometric View of Natural Intelligence     260
Boolean Networks     260
Random Boolean Networks     262
Discrete Digital and Continuous Analogue Domains     262
Summary     264
Mapping Natural Intelligence to Machine Space     269
Classical Architectures for Natural Intelligence     270
Learning, Knowledge, Knowing and Intelligence     271
Vectors, States, and Trajectories     273
Functions and Operators     275
Goal-seeking Intentional Behavior     277
Hierarchical Control     279
Control System Information Limitations     280
Biologically-Inspired Architectures: VLSI     282
Neuromorphic Architectures     284
Learning Algorithms     286
Self-Organizing Feature Map (SOFM)     287
The Problem of "Brittleness"     288
The Party     289
Noise and Uncertainty     293
The Role of Indexicals in Natural Intelligence     294
Problems with Pattern Recognition and Limits of Classification     295
Kinds of Space: Revisiting the Problem with Universals      299
Costs of Ignoring Phenomenological First-Person Experience     301
Problems with Complexity     303
Decidability     303
Computability of Rule-Governed and Rule-Bound Natural Intelligence     305
Recursively Enumerable Natural Intelligence     307
Summary     310
Summary and Conclusions of Self-Organizing Natural Intelligence     315
A History of Biased Intelligence Space     316
Natural Intelligence as Self-Organizing and Emerging     318
Multidimensional and Multilayered Intelligence     320
Three Major Kinds of Natural Intelligence     320
Nonlinear Methods for a Science of Intelligence     321
Some Issues Left Unresolved     324
The Problem of Universals     324
The Problem of Indexicals     325
The Problem of Awareness     325
The Problem of Autonomy     327
References     329
Index     355