作者: Mark Levene , Trevor Fenner
DOI: 10.1504/IJAISC.2011.042711
关键词: Computer science 、 Temporal difference learning 、 Sequential game 、 White (horse) 、 Evaluation function 、 Artificial intelligence 、 Computer chess 、 Style (sociolinguistics)
摘要: We describe a preliminary investigation into learning Chess player|s style from game records. The method is based on attempting to learn features of individual evaluation function using the temporal differences, with aid conventional engine architecture. Some encouraging results were obtained in styles two world champions, and we report our attempt use learnt discriminate between players records, by trying detect who was playing white black. also discuss some limitations approach.