Playing tic-tac-toe using a modified neural network and an improved genetic algorithm

H. K. Lam; S. H. Ling; Hung Fat Frank Leung; P. K.S. Tam; Y. S. Lee

doi:10.1109/IECON.2002.1185276

Playing tic-tac-toe using a modified neural network and an improved genetic algorithm

H. K. Lam
, S. H. Ling
, Hung Fat Frank Leung
, P. K.S. Tam
, Y. S. Lee

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

This paper presents an algorithm of playing game tic-tac-loc. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (CA). 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.

Original language	English
Title of host publication	IECON Proceedings (Industrial Electronics Conference)
Pages	1984-1989
Number of pages	6
DOIs	https://doi.org/10.1109/IECON.2002.1185276
Publication status	Published - 1 Dec 2002
Event	Proceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society - Sevilla, Spain Duration: 5 Nov 2002 → 8 Nov 2002

Conference

Conference	Proceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society
Country/Territory	Spain
City	Sevilla
Period	5/11/02 → 8/11/02

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

More information

10.1109/IECON.2002.1185276

http://hdl.handle.net/10397/1364

Cite this

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title = "Playing tic-tac-toe using a modified neural network and an improved genetic algorithm",

abstract = "This paper presents an algorithm of playing game tic-tac-loc. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (CA). 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.",

author = "Lam, \{H. K.\} and Ling, \{S. H.\} and Leung, \{Hung Fat Frank\} and Tam, \{P. K.S.\} and Lee, \{Y. S.\}",

year = "2002",

month = dec,

day = "1",

doi = "10.1109/IECON.2002.1185276",

language = "English",

pages = "1984--1989",

booktitle = "IECON Proceedings (Industrial Electronics Conference)",

note = "Proceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society ; Conference date: 05-11-2002 Through 08-11-2002",

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Lam, HK, Ling, SH, Leung, HFF, Tam, PKS & Lee, YS 2002, Playing tic-tac-toe using a modified neural network and an improved genetic algorithm. in IECON Proceedings (Industrial Electronics Conference). pp. 1984-1989, Proceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society, Sevilla, Spain, 5/11/02. https://doi.org/10.1109/IECON.2002.1185276

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AU - Lam, H. K.

AU - Ling, S. H.

AU - Leung, Hung Fat Frank

AU - Tam, P. K.S.

AU - Lee, Y. S.

PY - 2002/12/1

Y1 - 2002/12/1

N2 - This paper presents an algorithm of playing game tic-tac-loc. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (CA). 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.

AB - This paper presents an algorithm of playing game tic-tac-loc. This algorithm is learned by a modified neural network (NN), which is trained by an improved genetic algorithm (CA). 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.

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DO - 10.1109/IECON.2002.1185276

M3 - Conference article published in proceeding or book

SP - 1984

EP - 1989

BT - IECON Proceedings (Industrial Electronics Conference)

T2 - Proceedings of the 2002 28th Annual Conference of the IEEE Industrial Electronics Society

Y2 - 5 November 2002 through 8 November 2002

ER -

Playing tic-tac-toe using a modified neural network and an improved genetic algorithm

Abstract

Conference

ASJC Scopus subject areas

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