Playing Tic-Tac-Toe Using Genetic Neural Network with Double Transfer functions

Ling, SS; Lam, HK

Playing Tic-Tac-Toe Using Genetic Neural Network with Double Transfer functions

Ling, SS

Lam, HK

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Publisher:: Scientific Research Publishing, Inc.
Publication Type:: Journal Article
Citation:: Journal of Intelligence Learning Systems and Application, 2011, 3 (1), pp. 37 - 44
Issue Date:: 2011-01

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Field	Value	Language
dc.contributor.author	Ling, SS https://orcid.org/0000-0003-0849-5098	en_US
dc.contributor.author	Lam, HK	en_US
dc.date.issued	2011-01	en_US
dc.identifier.citation	Journal of Intelligence Learning Systems and Application, 2011, 3 (1), pp. 37 - 44	en_US
dc.identifier.issn	2150-8402	en_US
dc.identifier.uri	http://hdl.handle.net/10453/18269
dc.description.abstract	Computational intelligence is a powerful tool for game development. In this paper, an algorithm of playing the game Tic-Tac-Toe with computational intelligence is developed. This algorithm is learned by a Neural Network with Double Transfer functions (NNDTF), which is trained by genetic algorithm (GA). In the NNDTF, the neuron has two transfer functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the network. A Tic-Tac-Toe game is used to show that the NNDTF provide a better performance than the traditional neural network does.	en_US
dc.language	English	en_US
dc.publisher	Scientific Research Publishing, Inc.	en_US
dc.relation.ispartof	Journal of Intelligence Learning Systems and Application	en_US
dc.title	Playing Tic-Tac-Toe Using Genetic Neural Network with Double Transfer functions	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	3	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.issue	1	en_US
pubs.volume	3	en_US

Abstract:

Computational intelligence is a powerful tool for game development. In this paper, an algorithm of playing the game Tic-Tac-Toe with computational intelligence is developed. This algorithm is learned by a Neural Network with Double Transfer functions (NNDTF), which is trained by genetic algorithm (GA). In the NNDTF, the neuron has two transfer functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the network. A Tic-Tac-Toe game is used to show that the NNDTF provide a better performance than the traditional neural network does.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/18269