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Journal of Information Science and Engineering, Vol. 28 No. 1, pp. 145-159 (January 2012)

A Study on Genetic Algorithm and Neural Network for Mini-Games*

Department of Computer Science
National Chiao Tung University
Hsinchu, 300 Taiwan

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.

Keywords: artificial intelligence, evolutionary robotics, games, physics simulation, skill balancing

Full Text () Retrieve PDF document (201201_10.pdf)

Received February 28, 2011; revised August 19, 2011; accepted August 30, 2011.
Communicated by I-Chen Wu.
* This work was partially supported by the National Science Council of Taiwan, under Grant No. NSC 99-2221-E-009-143.