An integrated approach to achieving optimal design of computer games

Shang Hwa Hsu*, Feng Liang Lee, Muh-Cherng Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


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.

Original languageEnglish
Pages (from-to)145-149
Number of pages5
JournalExpert Systems with Applications
Issue number1
StatePublished - 1 Jul 2006


  • Computer game
  • Genetic algorithms
  • Neural networks
  • Optimization


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