Genetically Programmed Strategies For Chess Endgame

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)

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

10. Results • First experiment

12. Results • Fourth experiment

15. Results • Compute Strategy • Pattern