Ebook: Computational Intelligence in Games

The recent advances in computational intelligence paradigms have generated tremendous interest among researchers in the theory and implementation of games. Game theory involves the mathematical calculations and heuristics to optimize the efficient lines of play. This book presents the main constituents of computational intelligence paradigms including knowledge representation, probability-based approaches, fuzzy logic, neural networks, genetic algorithms, and rough sets. It includes a new approach of evolving a neural network to play checkers without human expertise. The book will be useful to researchers and practitioners who are interested in developing game techniques in computational intelligence environment.

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The recent advances in computational intelligence paradigms have generated tremendous interest among researchers in the theory and implementation of games. Game theory involves the mathematical calculations and heuristics to optimize the efficient lines of play. This book presents the main constituents of computational intelligence paradigms including knowledge representation, probability-based approaches, fuzzy logic, neural networks, genetic algorithms, and rough sets. It includes a new approach of evolving a neural network to play checkers without human expertise. The book will be useful to researchers and practitioners who are interested in developing game techniques in computational intelligence environment.

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The recent advances in computational intelligence paradigms have generated tremendous interest among researchers in the theory and implementation of games. Game theory involves the mathematical calculations and heuristics to optimize the efficient lines of play. This book presents the main constituents of computational intelligence paradigms including knowledge representation, probability-based approaches, fuzzy logic, neural networks, genetic algorithms, and rough sets. It includes a new approach of evolving a neural network to play checkers without human expertise. The book will be useful to researchers and practitioners who are interested in developing game techniques in computational intelligence environment.
Content:
Front Matter....Pages i-xii
Introduction to Computational Intelligence Paradigms....Pages 1-38
Evolving a Neural Network to Play Checkers without Human Expertise....Pages 39-56
Retrograde Analysis of Patterns versus Metaprogramming....Pages 57-75
Learning to Evaluate Go Positions via Temporal Difference Methods....Pages 77-98
Model-Based Reinforcement Learning for Evolving Soccer Strategies....Pages 99-132
Fuzzy Rule-Based Strategy for a Market Selection Game....Pages 133-156
Back Matter....Pages 157-161

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The recent advances in computational intelligence paradigms have generated tremendous interest among researchers in the theory and implementation of games. Game theory involves the mathematical calculations and heuristics to optimize the efficient lines of play. This book presents the main constituents of computational intelligence paradigms including knowledge representation, probability-based approaches, fuzzy logic, neural networks, genetic algorithms, and rough sets. It includes a new approach of evolving a neural network to play checkers without human expertise. The book will be useful to researchers and practitioners who are interested in developing game techniques in computational intelligence environment.
Content:
Front Matter....Pages i-xii
Introduction to Computational Intelligence Paradigms....Pages 1-38
Evolving a Neural Network to Play Checkers without Human Expertise....Pages 39-56
Retrograde Analysis of Patterns versus Metaprogramming....Pages 57-75
Learning to Evaluate Go Positions via Temporal Difference Methods....Pages 77-98
Model-Based Reinforcement Learning for Evolving Soccer Strategies....Pages 99-132
Fuzzy Rule-Based Strategy for a Market Selection Game....Pages 133-156
Back Matter....Pages 157-161
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