Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1364
Title: Playing tic-tac-toe using a modified neural network and an improved genetic algorithm
Authors: Lam, HK
Ling, SH
Leung, FHF 
Tam, PKS
Lee, YS
Keywords: Game theory
Genetic algorithms
Knowledge based systems
Learning algorithms
Neural networks
Transfer functions
Issue Date: 2002
Publisher: IEEE
Source: IECON-2002 : proceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society, Sevilla, Spain, November 5-8, 2002, p. 1984-1989 How to cite?
Abstract: This paper presents an algorithm of playing game tic-tac-toc. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (GA). In the proposed NN, the neuron has two activation functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the network. It will be shown that the proposed NN and GA provide a better performance than the traditional approach.
URI: http://hdl.handle.net/10397/1364
ISBN: 0-7803-7474-6
Rights: © 2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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