Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/8205| Title: | An evolutionary tic-tac-toe player |
| Authors: | Al-Khateeb, Belal |
| Keywords: | artificial neural networks tic-tac-toe evolutionary algorithms |
| Issue Date: | 4-Nov-2012 |
| Publisher: | Int. J. Reasoning-based Intelligent Systems |
| Abstract: | In this paper, artificial neural networks are used as function evaluators in order to evolve game playing strategies for the game of tic-tac-toe. The best evolved player is tested against an online perfect tic-tac-toe player, and also against a nearly perfect player which allows 10% random moves and finally against five selected human players. Those players are with different playing abilities. The results are promising, suggesting many other research directions. |
| URI: | http://localhost:8080/xmlui/handle/123456789/8205 |
| Appears in Collections: | قسم علوم الحاسبات |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| IJRIS40401_Al-Khateeb.pdf | 172.25 kB | Adobe PDF | View/Open |
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