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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Davis, J.E. Kendall, G. |
| Copyright Year | 2002 |
| Description | Author affiliation: Optimisation & Planning Res. Group, Nottingham Univ., UK (Davis, J.E.; Kendall, G.) |
| Abstract | Awari is a two-player game of perfect information, played using 12 "pits" and 48 seeds or stones. The aim is for one player to capture more than half the seeds. In this work we show how an awari player can be evolved using a co-evolutionary approach where computer players play against one another, with the strongest players surviving and being mutated using an evolutionary strategy (ES). The players are represented using a simple evaluation function, representing the current game state, with each term of the function having a weight which is evolved using the ES. The output of the evaluation function is used in a mini-max search. We play the best evolved player against one of the strongest shareware programs (Awale) and are able to defeat the program at three of its four levels of play. |
| Sponsorship | IEEE IEEE Neural Networks Soc. IEE Evolutionary Programming Soc |
| Starting Page | 1408 |
| Ending Page | 1413 |
| File Size | 616076 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780372824 |
| DOI | 10.1109/CEC.2002.1004449 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2002-05-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Artificial neural networks Artificial intelligence Databases Processor scheduling Computer science History Hardware Internet Bridges |
| Content Type | Text |
| Resource Type | Article |
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