A study on genetic algorithm and neural network for mini-games

Sai-Keung Wong*, Shih Wei Fang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Physics simulation and character control are two important issues in computer games. In this paper, we propose two games which are tailored for investigating some aspects of these two issues. We study on the applications of neural network and the genetic algorithm techniques for building the controllers and the controllers should be able to finish the specific tasks in the two games. The goal of the first game is that the controller can shoot a ball so that the ball collides with the other two balls one after another. The challenge of this game is that the ball should be shot from the proper position and the goal is achieved every time. The second game is a duel game and two virtual characters are controlled to fight with each other. We develop a method for verifying whether or not the skill power of the two virtual characters is balanced. The controllers of both games are evolved based on neural network and genetic algorithm in an unsupervised learning manner. We perform a comprehensive study on the performance and weaknesses of the controllers.

Original languageEnglish
Pages (from-to)145-159
Number of pages15
JournalJournal of Information Science and Engineering
Issue number1
StatePublished - 1 Jan 2012


  • Artificial intelligence
  • Evolutionary robotics
  • Games
  • Physics simulation
  • Skill balancing


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