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An adaptation of social Learning in evolutionary computation for tic-tac-toe.

Yaakob, Razali and Kendall, Graham (2009) An adaptation of social Learning in evolutionary computation for tic-tac-toe. International Journal of Computer Science and Network Security, 9 (9). pp. 294-300. ISSN 1738-7906

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Abstract

This paper investigates an integration of individual and social learning, utilising evolutionary neural networks, in order to evolve game playing strategies. Individual learning enables players to create their own strategies. Then, we allow the use of social learning to allow poor performing players to learn from players which are playing at a higher level. The feed forward neural networks are evolved via evolution strategies. The evolved neural network players play first and compete against a nearly perfect player. At the end of each game, the evolved players receive a score based on whether they won, lost or drew. Our results demonstrate that the use of social learning helps players learn strategies, which are superior to those evolved when social learning is not utilised.

Item Type:Article
Keyword:Evolutionary strategies; Neural network; Individual learning; Social learning; Tic-Tac-Toe
Subject:Neural networks (Computer science).
Subject:Evolutionary programming (Computer science).
Subject:Evolutionary computation.
Faculty or Institute:Faculty of Computer Science and Information Technology
ID Code:13005
Deposited By: Umikalthom Abdullah
Deposited On:10 Feb 2012 16:16
Last Modified:10 Feb 2012 16:16

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