Swarm intelligence
Traditional methods for creating intelligent computational systems haveprivileged private ""internal"" cognitive and computational processes. Incontrast, Swarm Intelligence argues that humanintelligence derives from the interactions of individuals in a social worldand further, th...
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| Otros Autores: | , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
San Francisco :
Morgan Kaufmann Publishers
c2001.
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| Colección: | Morgan Kaufmann series in evolutionary computation.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627945806719 |
Tabla de Contenidos:
- Preface; A Thumbnail Sketch of Particle Swarm Optimization; What This Book Is, and Is Not, About; Assertions; Organization of the Book; Software; Definitions; Acknowledgments; Part One Foundations; 1 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 CriterionIntelligence in Machines: The Turing Criterion; 2 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:; 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
- 3 On Our Nonexistence as Entities: The Social OrganismViews 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; 4 Evolutionary Computation Theory and Paradigms; Introduction; Evolutionary Computation History
- The Four Areas of Evolutionary ComputationGenetic 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 ProgrammingSummary; 5 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; Latan''s Dynamic Social Impact Theory
- Boyd and Richerson's Evolutionary Culture Model
