An integrated approach to achieving optimal design of computer games

Submitted by Jason Rutter on Fri, 09/03/2007 - 21:07.

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Publication Type		Journal Article
Year of Publication		2006
Authors		Hsu, S. H.; Lee, F. L.; Wu, M. C.
Journal Title		Expert Systems with Applications
Volume		31
Pagination		145-149
ISBN Number		0957-4174
Accession Number		ISI:000236903700016
Key Words		neural networks; genetic algorithms; optimization; computer game; artificial neural-networks; genetic algorithms; support-system; optimization
Abstract		In a time-to-market environment, designers may not be able to incorporate all the design features in a computer game. For each feature, there are several levels of implementation, which is corresponded to different levels of benefit as well as cost. Therefore, a trade-off decision for determining appropriate levels of implementation is very important, yet has been rarely studied in literature. This paper presents an approach to solve the trade-off decision problem. This approach applies the neural network technique and develops a genetic algorithm to optimize the design of computer games. By this approach, a near-optimal design alternative can be identified in a timely fashion.

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Submitted by hayel (not verified) on Sun, 18/11/2007 - 06:49.

this article is very helpful for my researches

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