Using Genetic Algorithm to Solve Game of Go-Moku

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IJCA Special Issue on Optimization and On-chip Communication
© 2012 by IJCA Journal
ooc - Number 1
Year of Publication: 2012
Authors:
Sanjay M Shah
Dharm Singh
J.S Shah

Sanjay M Shah, Dharm Singh and J S Shah. Article: Using Genetic Algorithm to Solve Game of Go-Moku. IJCA Special Issue on Optimization and On-chip Communication ooc(1):28-31, February 2012. Full text available. BibTeX

@article{key:article,
	author = {Sanjay M Shah and Dharm Singh and J.S Shah},
	title = {Article: Using Genetic Algorithm to Solve Game of Go-Moku},
	journal = {IJCA Special Issue on Optimization and On-chip Communication},
	year = {2012},
	volume = {ooc},
	number = {1},
	pages = {28-31},
	month = {February},
	note = {Full text available}
}

Abstract

Genetic algorithm is a stochastic parallel beam search that can be applied to many typical search problems. This paper describes a genetic algorithmic approach to a problem in artificial intelligence. During the process of evolution, the environment cooperates with the population by continuously making itself friendlier so as to lower the evolutionary pressure. Evaluations show the performance of this approach seems considerably effective in solving this type of board games. Game-playing programs are often described as being a combination of search and knowledge. Board Games provide dynamic environments that make them ideal area of computational intelligence theories, architectures, and algorithms. Evolutionary algorithms such as Genetic algorithm are applied to the game playing because of the very large state space of the problem. This paper mainly highlights how genetic algorithm can be applied to game of Go-moku.

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