| Previous | [ 1] | [ 2] | [ 3] | [ 4] | [ 5] | [ 6] | [ 7] | [ 8] | [ 9] | [ 10] | [ 11] | [ 12] | [ 13] |
¡@
SAI-KEUNG WONG AND SHIH-WEI FANG
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.
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.