Computer-simulation gaming systems utilizing neural networks and genetic algorithms
Norio Baba, Tomio Kita, Yusuke Takagawara, Yoichi Erikawa, Kazuhiro ODA · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
In recent years, neural networks and genetic algorithms (GAs) have been studied quite extensively by many researchers. They have been applied to various actual problems. In this paper, neural networks and GAs are applied to the computer gaming system which is the modified version of the COMMONS GAME. It is shown that neural network technology is quite helpful for making a copy of each player's strategy in game playing. It is also shown that GAs can be utilized for making the game playing exciting. Further, applications of neural networks and GAs to the familiar computer simulation games `Nobunaga's Ambition' and `Sangokushi' are briefly introduced in the final part of this paper.