An evolutionary tic-tac-toe player Online publication date: Sun, 27-Jan-2013
by Belal Al-Khateeb
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 4, No. 4, 2012
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.
Online publication date: Sun, 27-Jan-2013
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Reasoning-based Intelligent Systems (IJRIS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org