ICGA Journal · 1997 · 36 citations · 0 references
Artificial IntelligenceEngineeringMachine LearningChess PiecesSequential LearningGame TheoryRelative ValuesIntelligent SystemsData SciencePattern RecognitionTemporal DataEvaluation FunctionRobot LearningGeneral Game PlayingCognitive ScienceTemporal Pattern RecognitionSequential Decision MakingComputer ScienceExploration V ExploitationComputer VisionTemporal Difference
This paper describes experiments where we attempt to learn the relative values of chess pieces by the use of temporal difference learning applied to minimax searches. We show that we are able to learn suitable piece values, and that these values perform at least as well as piece values widely quote d in elementary chess books.