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Genetically Programmed Strategies for Chess Endgame: Evolution of Effective KRK Tactics

This paper introduces genetically programmed strategies for the chess endgame, focusing on evolving effective strategies for the KRK scenario. It discusses the background of chess computing, the move tree, evaluation functions, and genetic algorithms utilizing neural networks. By using genetic programming and fitness functions, the paper aims to generate correct and effective strategies for KRK that outperform brute-force algorithms. The approach involves encoding strategies in binary trees with operators as nodes and moves as leaves, enabling the use of if-then-else logic for decision-making. The fitness of strategies is evaluated based on game value, total moves, and program tree size. The results of experiments showcase the efficacy of the evolved strategies, emphasizing the importance of pattern recognition and neural network-based evolution in improving chess endgame tactics.

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Genetically Programmed Strategies for Chess Endgame: Evolution of Effective KRK Tactics

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Presentation Transcript

  1. Genetically Programmed Strategies For Chess Endgame

  2. Introduction • Backgroud • Evolving Strategies For KRK • Results

  3. Background • Computing • Brute-Force Algorithm • PatternUse DataBase instead of BFA • Unstandable Readable • Alpha-Beta pruning Algorithm • Improve evalution function • Genetic Algorithm by neural network

  4. Evolving Strategies For KRK • Focus on tree of moves and evalution functions not algorithm and not table • Learn how to play effectively use patten • Use Genetic Programming (GP) • Compute Correct Strategy • Generate an effective strategy with fitness function (outcome)

  5. Evolving Strategies For KRK • Pattern:good enough for strategy • Genetic encoding and genetic operator • Binary Tree with operator-strategy • Operator as Node; Function(moves) as Leaves • Each Operator can be read use if-then-else • Transition(node-node) use logical AND • Mutation(replace operator by random)

  6. Evolving Strategies For KRK • Fitness: • fi:partical better game value • Mi:total moves • N:program tree size

  7. Results • First experiment

  8. Results • Fourth experiment

  9. Results • Compute Strategy • Pattern

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