| |
| |
| Preface | |
| |
| |
| |
| Foundations | |
| |
| |
| |
| Models and Concepts of Life and Intelligence | |
| |
| |
| The Mechanics of Life and Thought | |
| |
| |
| Stochastic Adaptation: Is Anything Ever Really Random? | |
| |
| |
| The "Two Great Stochastic Systems" | |
| |
| |
| The Game of Life: Emergence in Complex Systems | |
| |
| |
| The Game of Life | |
| |
| |
| Emergence | |
| |
| |
| Cellular Automata and the Edge of Chaos | |
| |
| |
| Artificial Life in Computer Programs | |
| |
| |
| Intelligence: Good Minds in People and Machines | |
| |
| |
| Intelligence in People: The Boring Criterion | |
| |
| |
| Intelligence in Machines: The Turing Criterion | |
| |
| |
| |
| Symbols, Connections, and Optimization by Trial and Error | |
| |
| |
| Symbols in Trees and Networks | |
| |
| |
| Problem Solving and Optimization | |
| |
| |
| A Super-Simple Optimization Problem | |
| |
| |
| Three Spaces of Optimization | |
| |
| |
| Fitness Landscapes | |
| |
| |
| High-Dimensional Cognitive Space and Word Meanings | |
| |
| |
| Two Factors of Complexity: NK Landscapes | |
| |
| |
| Combinatorial Optimization | |
| |
| |
| Binary Optimization | |
| |
| |
| Random and Greedy Searches | |
| |
| |
| Hill Climbing | |
| |
| |
| Simulated Annealing | |
| |
| |
| Binary and Gray Coding | |
| |
| |
| Step Sizes and Granularity | |
| |
| |
| Optimizing with Real Numbers | |
| |
| |
| Summary | |
| |
| |
| |
| On Our Nonexistence as Entities: The Social Organism | |
| |
| |
| Views of Evolution | |
| |
| |
| Gaia: The Living Earth | |
| |
| |
| Differential Selection | |
| |
| |
| Our Microscopic Masters? | |
| |
| |
| Looking for the Right Zoom Angle | |
| |
| |
| Flocks, Herds, Schools, and Swarms: Social Behavior as Optimization | |
| |
| |
| Accomplishments of the Social Insects | |
| |
| |
| Optimizing with Simulated Ants: Computational Swarm Intelligence | |
| |
| |
| Staying Together but Not Colliding: Flocks, Herds, and Schools | |
| |
| |
| Robot Societies | |
| |
| |
| Shallow Understanding | |
| |
| |
| Agency | |
| |
| |
| Summary | |
| |
| |
| |
| Evolutionary Computation Theory and Paradigms | |
| |
| |
| Introduction | |
| |
| |
| Evolutionary Computation History | |
| |
| |
| The Four Areas of Evolutionary Computation | |
| |
| |
| Genetic Algorithms | |
| |
| |
| Evolutionary Programming | |
| |
| |
| Evolution Strategies | |
| |
| |
| Genetic Programming | |
| |
| |
| Toward Unification | |
| |
| |
| Evolutionary Computation Overview | |
| |
| |
| EC Paradigm Attributes | |
| |
| |
| Implementation | |
| |
| |
| Genetic Algorithms | |
| |
| |
| An Overview | |
| |
| |
| A Simple GA Example Problem | |
| |
| |
| A Review of GA Operations | |
| |
| |
| Schemata and the Schema Theorem | |
| |
| |
| Final Comments on Genetic Algorithms | |
| |
| |
| Evolutionary Programming | |
| |
| |
| The Evolutionary Programming Procedure | |
| |
| |
| Finite State Machine Evolution | |
| |
| |
| Function Optimization | |
| |
| |
| Final Comments | |
| |
| |
| Evolution Strategies | |
| |
| |
| Mutation | |
| |
| |
| Recombination | |
| |
| |
| Selection | |
| |
| |
| Genetic Programming | |
| |
| |
| Summary | |
| |
| |
| |
| Humans--Actual, Imagined, and Implied | |
| |
| |
| Studying Minds | |
| |
| |
| The Fall of the Behaviorist Empire | |
| |
| |
| The Cognitive Revolution | |
| |
| |
| Bandura's Social Learning Paradigm | |
| |
| |
| Social Psychology | |
| |
| |
| Lewin's Field Theory | |
| |
| |
| Norms, Conformity, and Social Influence | |
| |
| |
| Sociocognition | |
| |
| |
| Simulating Social Influence | |
| |
| |
| Paradigm Shifts in Cognitive Science | |
| |
| |
| The Evolution of Cooperation | |
| |
| |
| Explanatory Coherence | |
| |
| |
| Networks in Groups | |
| |
| |
| Culture in Theory and Practice | |
| |
| |
| Coordination Games | |
| |
| |
| The El Farol Problem | |
| |
| |
| Sugarscape | |
| |
| |
| Tesfatsion's ACE | |
| |
| |
| Picker's Competing-Norms Model | |
| |
| |
| Latane's Dynamic Social Impact Theory | |
| |
| |
| Boyd and Richerson's Evolutionary Culture Model | |
| |
| |
| Memetics | |
| |
| |
| Memetic Algorithms | |
| |
| |
| Cultural Algorithms | |
| |
| |
| Convergence of Basic and Applied Research | |
| |
| |
| Culture--and Life without It | |
| |
| |
| Summary | |
| |
| |
| |
| Thinking Is Social | |
| |
| |
| Introduction | |
| |
| |
| Adaptation on Three Levels | |
| |
| |
| The Adaptive Culture Model | |
| |
| |
| Axelrod's Culture Model | |
| |
| |
| |
| Similarity in Axelrod's Model | |
| |
| |
| |
| Optimization of an Arbitrary Function | |
| |
| |
| |
| A Slightly Harder and More Interesting Function | |
| |
| |
| |
| A Hard Function | |
| |
| |
| |
| Parallel Constraint Satisfaction | |
| |
| |
| |
| Symbol Processing | |
| |
| |
| Discussion | |
| |
| |
| Summary | |
| |
| |
| |
| The Particle Swarm and Collective Intelligence | |
| |
| |
| |
| The Particle Swarm | |
| |
| |
| Sociocognitive Underpinnings: Evaluate, Compare, and Imitate | |
| |
| |
| Evaluate | |
| |
| |
| Compare | |
| |
| |
| Imitate | |
| |
| |
| A Model of Binary Decision | |
| |
| |
| Testing the Binary Algorithm with the De Jong Test Suite | |
| |
| |
| No Free Lunch | |
| |
| |
| Multimodality | |
| |
| |
| Minds as Parallel Constraint Satisfaction Networks in Cultures | |
| |
| |
| The Particle Swarm in Continuous Numbers | |
| |
| |
| The Particle Swarm in Real-Number Space | |
| |
| |
| Pseudocode for Particle Swarm Optimization in Continuous Numbers | |
| |
| |
| Implementation Issues | |
| |
| |
| An Example: Particle Swarm Optimization of Neural Net Weights | |
| |
| |
| A Real-World Application | |
| |
| |
| The Hybrid Particle Swarm | |
| |
| |
| Science as Collaborative Search | |
| |
| |
| Emergent Culture, Immergent Intelligence | |
| |
| |
| Summary | |
| |
| |
| |
| Variations and Comparisons | |
| |
| |
| Variations of the Particle Swarm Paradigm | |
| |
| |
| Parameter Selection | |
| |
| |
| Controlling the Explosion | |
| |
| |
| Particle Interactions | |
| |
| |
| Neighborhood Topology | |
| |
| |
| Substituting Cluster Centers for Previous Bests | |
| |
| |
| Adding Selection to Particle Swarms | |
| |
| |
| Comparing Inertia Weights and Constriction Factors | |
| |
| |
| Asymmetric Initialization | |
| |
| |
| Some Thoughts on Variations | |
| |
| |
| Are Particle Swarms Really a Kind of Evolutionary Algorithm? | |
| |
| |
| Evolution beyond Darwin | |
| |
| |
| Selection and Self-Organization | |
| |
| |
| Ergodicity: Where Can It Get from Here? | |
| |
| |
| Convergence of Evolutionary Computation and Particle Swarms | |
| |
| |
| Summary | |
| |
| |
| |
| Applications | |
| |
| |
| Evolving Neural Networks with Particle Swarms | |
| |
| |
| Review of Previous Work | |
| |
| |
| Advantages and Disadvantages of Previous Approaches | |
| |
| |
| The Particle Swarm Optimization Implementation Used Here | |
| |
| |
| Implementing Neural Network Evolution | |
| |
| |
| An Example Application | |
| |
| |
| Conclusions | |
| |
| |
| Human Tremor Analysis | |
| |
| |
| Data Acquisition Using Actigraphy | |
| |
| |
| Data Preprocessing | |
| |
| |
| Analysis with Particle Swarm Optimization | |
| |
| |
| Summary | |
| |
| |
| Other Applications | |
| |
| |
| Computer Numerically Controlled Milling Optimization | |
| |
| |
| Ingredient Mix Optimization | |
| |
| |
| Reactive Power and Voltage Control | |
| |
| |
| Battery Pack State-of-Charge Estimation | |
| |
| |
| Summary | |
| |
| |
| |
| Implications and Speculations | |
| |
| |
| Introduction | |
| |
| |
| Assertions | |
| |
| |
| Up from Social Learning: Bandura | |
| |
| |
| Information and Motivation | |
| |
| |
| Vicarious versus Direct Experience | |
| |
| |
| The Spread of Influence | |
| |
| |
| Machine Adaptation | |
| |
| |
| Learning or Adaptation? | |
| |
| |
| Cellular Automata | |
| |
| |
| Down from Culture | |
| |
| |
| Soft Computing | |
| |
| |
| Interaction within Small Groups: Group Polarization | |
| |
| |
| Informational and Normative Social Influence | |
| |
| |
| Self-Esteem | |
| |
| |
| Self-Attribution and Social Illusion | |
| |
| |
| Summary | |
| |
| |
| |
| And in Conclusion... | |
| |
| |
| |
| Statistics for Swarmers | |
| |
| |
| |
| Genetic Algorithm Implementation | |
| |
| |
| Glossary | |
| |
| |
| References | |
| |
| |
| Index | |