Self-organizing natural intelligence : issues of knowing, meaning, and complexity / by Myrna Estep.

Format:

Book

Author/Creator:

Estep, Myrna.

Language:

English

Subjects (All):

Intellect.

Self-organizing systems.

Knowledge, Theory of.

Physical Description:

xxxii, 359 pages : illustrations ; 25 cm

Place of Publication:

Dordrecht : Springer, [2006]

Summary:

Self-Organizing Natural Intelligence brings new scientific methods to intelligence research that is currently under the influence of largely classical 19th century single causal theory and method. This out-dated classical approach has resulted in the single-capacity g-theory, a "central processor", top-down, genetically determined linguistic view of intelligence that is directly contradicted by empirical facts of human and animal studies of intelligence.

This book proposes, utilizes, and demonstrates the research superiority of a highly developed multidisciplinary theory models approach to intelligence. With conceptual tools, concepts and mathematical methods more suited to continuous, dynamic phenomena of living things, the entire scope of natural intelligence based upon empirical studies of actual human and animal experience is addressed. Results show that human and animal intelligence is largely self-organizing and emergent across a spectrum of major categories of kinds of natural intelligence, not limited to a single "top down" capacity as current proponents of the single-capacity g-theory and IQ approach support.

Contrary to the single-capacity verbal theory of intelligence, his work argues and shows evidence for three major categories of natural intelligence. Overwhelming empirical evidence is given to show that our understanding of cognition itself must be broadened to include nonverbal immediate awareness as a category of natural intelligence that is embedded within sensory and somatosensory motor processes that make possible yet another category of intelligence, knowing how.

While most current theories of intelligence assume that the mind is entirely computational, and also assume that sensation is cognitively "neutral" having no intentionality, here empirical evidence is presented from numerous clinical studies showing that certain primitive sensory processes are not cognitively neutral, nor do they require a representational language interface in order to be accessible to cognitive (intelligence) processes. This volume describes a rigorous treatment and exhaustive classification of natural intelligence while also demonstrating a more adequate scientific and mathematical approach than current statistical and psychometric approaches shoring up the out-dated and misused IQ hypothetical construct.

Contents:

1 The Problem of Intelligence 1

1.1 Some of the Basic Issues 4

The Single and Multiple Capacity Views 5

Where Are the Facts of Intelligence Found? 6

1.2 The Faulty Sciences of Intelligence 7

1.2.1 The Anti-Theory Bias 8

A Misleading Heritage of Inductivism 8

Confusing Cause and Correlation 9

1.2.2 Invalid Reductionism 10

The Faulty Genetic Argument 11

A Neo-Darwinist Influence 12

1.2.3 Neglect of Emerging Intelligence 14

Inadequacies of the Classical Linear Approach 15

1.2.4 Neglect of Theory Construction and Concept Formation 16

Mechanism and Organicism 17

Narrowing the Intelligence Domain to Suit Tools At Hand 21

1.2.5 Unexamined Assumptions, Concepts, and Fallacies 21

The Scope of Cognition 22

1.2.6 A Bankrupt Theory of Knowing in the Sciences of Intelligence 25

Kinds of Knowing and the Intellectualist Legend 26

1.2.7 A Missing Distinction between Rule-governed and Rule-bound Intelligence 27

1.2.8 Neglect of Multiple Signs and Disclosure of Intelligence 29

Signals, Cues, and Clues 29

Exhibiting and Disclosing Intelligence 30

1.2.9 Mechanical "Hard-Wired" and Natural Intelligence: Absent the Difference 32

1.3 Requirements for a New Science of Intelligence 33

1.3.1 A Broader Theory of Knowing 34

Knowledge That, Knowing How, Immediate Awareness 34

1.3.2 A Broader Theory of Signs of Intelligence 37

Toward Three-Dimensional Signs and Patterns 38

1.3.3 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

2 The Universe of Intelligence 49

2.1 Carving the Problem Space 49

2.1.1 Rational Inquiry and Ideology: The Differences 50

2.1.2 Careless Carving 52

2.2 Classical Origins and Fabric of Intelligence Theory: Cut on Biases 53

2.2.1 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

2.2.2 Anthropocentrism, Language, Gender, Race, Size, Wealth, and Place 58

The Intrinsic and Instrumental Intelligence Difference 59

The Intelligence Center of the Universe 59

2.2.3 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

2.3 Today's IQ Tests: Circularity, Bias, and American Eugenics 73

2.3.1 The Economic Argument 74

The Issue of Test Validity 75

2.3.2 Reification and the Eugenics Argument 76

2.3.3 A Static Hierarchy: g the Controller 78

Missing From g: Experience 80

2.3.4 Biological Determinism Revisited 83

Neo-Darwinism and the Heritability Argument 83

A Short History of Rising IQ Scores 87

Suspect Racial Sorting 89

3 The Genesis of Intelligence: Innate and Emergence Arguments 93

3.1 Categorization, Classification, Concepts and Representation 93

3.1.1 Reality and the Influence of Representationalism 95

3.2 The Continuing Problem with Universals (Concepts): Some History 96

Plato 96

Aristotle 99

3.2.1 Realists, Conceptualists, and Nominalists on Universals 101

3.2.2 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

3.2.3 Today's Representationalist Myths: Cognitive Maps in the Brain 110

3.3 The Innate Versus Emergence Arguments 113

3.3.1 The Genetically Encoded Syntax Argument 113

3.3.2 Nonverbal Communication: Beyond Alphanumeric Symbols and Vocalizations 115

Gestures 116

From Manual Gestures to Whole Body Performances 118

3.3.3 Evolutionary Argument against Innatists 120

3.3.4 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

4 The Intelligence of Doing: Sensorimotor Domains and Knowing How 131

4.1 The Intelligence of Doing 131

4.1.1 A Two-Pronged Approach to Intelligence Inquiry 133

Fallacies to Avoid 134

4.1.2 Cognition, Consciousness, Awareness 136

4.2 The Science of Awareness 138

4.2.1 Cortical Structures and Information: Neural Bases of Awareness and Intelligent Doing 140

Reticulo-Thalamo-Cortical (RTC) System 143

4.2.2 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

4.2.3 Primitive Awareness 147

Scientific Definitions of "Awareness" 148

Possible Subject Bias 149

Awareness of and Awareness that 150

4.2.4 Experimental Evidence of Immediate Awareness 150

Evidence of Awareness Under Anesthesia 154

What the Experiments Show 156

4.2.5 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

4.3 Primitive Intelligence of Moving and Touching 167

4.3.1 Multiple Spaces of the Senses, Images and Probing 168

4.3.2 Smoothness and Timing in Intelligent Doing 173

Limitations of Computational Models of Awareness: Selection without Classification 174

Where We Enter the Circle of Cognition: Immediate Awareness 176

Primitive Selection and Problems with Consciousness 178

5 Universals, Mathematical Thought and Awareness 181

5.1 On the Origins and Nature of Mathematical Thought 182

The Genetic Fallacy 183

5.1.1 A Postmodern View: The Body Shapes Development and Content of Mathematics 184

Conceptual Metaphors and Begging the Question 187

5.1.2 The Language Causal Argument: Language Shapes the Development and Content of Mathematics 188

The Neurological Evidence 190

5.1.3 Thinking in Patterns and Images 192

Mathematical Thought and Space 193

Space and Theorem-Proving 194

5.1.4 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

5.2 Problems with Representation Theories Revisited 204

Naming, Indexes, Classification, Sets, Kinds and Types 205

5.2.1 Classification and the Nature of Sui Generis Objects of Immediate Awareness 208

5.3 Phenomenal Experience and Mathematics 209

Demonstrating the Problem with Indexicals 211

Retroduction, Reality and Non-algorithmic Insight 212

5.3.1 Perception and Mathematical Objects 213

5.3.2 The Reality of Sets and Concepts 215

5.3.3 Intersubjective Requirements of Mathematical Thought 218

6 Intelligence as Self-Organizing Emerging Complexity 223

6.1 Categories of Natural Intelligence 223

6.2 Self-Organization and Pattern Formation 224

Emergence 226

6.2.1 Interactive Systems and Self-Organization 227

Complexity 228

6.3 Mechanism and Organicism Revisited 230

6.3.1 Organized Simplicity and Unorganized Complexity 230

6.3.2 Organized Complexity 232

Causality 234

6.4 Nonlinear Theory Models Approach to Natural Intelligence 235

6.4.1 The SIGGS Theory Model 238

6.4.2 Information

Theory 240

Information-Theoretic Extensions of Simple Feedback Model 242

6.5 SIGGS Applied to Natural Intelligence Systems 244

Elements and Signs of Natural Intelligence 244

6.5.1 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

6.5.2 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

6.6 From a Symbol-based View to a Geometric View of Natural Intelligence 260

6.6.1 Boolean Networks 260

Random Boolean Networks 262

Discrete Digital and Continuous Analogue Domains 262

7 Mapping Natural Intelligence to Machine Space 269

7.1 Classical Architectures for Natural Intelligence 270

7.1.1 Learning, Knowledge, Knowing and Intelligence 271

Vectors, States, and Trajectories 273

Functions and Operators 275

7.1.2 Goal-seeking Intentional Behavior 277

Hierarchical Control 279

7.1.3 Control System Information Limitations 280

7.2 Biologically-Inspired Architectures: VLSI 282

7.2.1 Neuromorphic Architectures 284

Learning Algorithms 286

Self-Organizing Feature Map (SOFM) 287

7.2.2 The Problem of "Brittleness" 288

The Party 289

Noise and Uncertainty 293

The Role of Indexicals in Natural Intelligence 294

7.2.3 Problems with Pattern Recognition and Limits of Classification 295

7.2.4 Kinds of Space: Revisiting the Problem with Universals 299

Costs of Ignoring Phenomenological First-Person Experience 301

7.3 Problems with Complexity 303

7.3.1 Decidability 303

Computability of Rule-Governed and Rule-Bound Natural Intelligence 305

Recursively Enumerable Natural Intelligence 307

8 Summary and Conclusions of Self-Organizing Natural Intelligence 315

8.1 A History of Biased Intelligence Space 316

8.2 Natural Intelligence as Self-Organizing and Emerging 318

8.2.1 Multidimensional and Multilayered Intelligence 320

8.2.2 Three Major Kinds of Natural Intelligence 320

8.3 Nonlinear Methods for a Science of Intelligence 321

8.4 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.

Notes:

Includes bibliographical references (pages 329-353) and index.

ISBN:

9781402052750

OCLC:

75927222

Publisher Number:

9781402052750