The recent advances in computational intelligence paradigms have generates tremendous interest among researchers in the theory and implementation of games....
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Résumé
The recent advances in computational intelligence paradigms have generates 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 arrested in developing games techniques in computational, intelligence environment.
Sommaire
Evolving a neural network to play checkers without human expertise
Retrograde analysis of patterns versus metaprogramming
Learning to evaluate Go positions via temporal difference methods
Model-based reinforcement learning for evolving soccer strategies
Fuzzy rule-based strategy for a market selection game