Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
534891 | Pattern Recognition Letters | 2008 | 6 Pages |
Abstract
In this paper, we introduce a chess program able to adapt its game strategy to its opponent, as well as to adapt the evaluation function that guides the search process according to its playing experience. The adaptive and learning abilities have been implemented through Bayesian networks. We show how the program learns through an experiment consisting on a series of games that point out that the results improve after the learning stage.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Antonio Fernández, Antonio Salmerón,