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


Citation

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

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.


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Additional Metadata

Item Type: Article
Subject: Neural networks (Computer science).
Subject: Evolutionary programming (Computer science).
Subject: Evolutionary computation.
Divisions: Faculty of Computer Science and Information Technology
Keywords: Evolutionary strategies; Neural network; Individual learning; Social learning; Tic-Tac-Toe
Depositing User: Umikalthom Abdullah
Date Deposited: 10 Feb 2012 08:16
Last Modified: 03 Nov 2015 01:51
URI: http://psasir.upm.edu.my/id/eprint/13005
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