Comparison of AI Techniques for Fighting Action Games - Genetic Algorithms/Neural Networks/Evolutionary Neural Networks

Recently many studies have attempted to implement intelligent characters for fighting action games. They used genetic algorithms, neural networks, and evolutionary neural networks to create intelligent characters. This study quantitatively compared the performance of these three AI techniques in the same game and experimental environments, and analyzed the results of experiments. As a result, neural network and evolutionary neural network showed excellent performance in the final convergence score ratio while evolutionary neural network and genetic algorithms showed excellent performance in convergence speed. In conclusion, evolutionary neural network which showed excellent results in both the final convergence score ratio and the convergence score is most appropriate AI technique for fighting action games.

[1]  Sung Hoon Jung,et al.  Adaptation of Intelligent Characters to Changes of Game Environments , 2005, CIS.

[2]  D. B. Fogel,et al.  Using evolutionary programing to create neural networks that are capable of playing tic-tac-toe , 1993, IEEE International Conference on Neural Networks.

[3]  Daniel M. Johnson,et al.  Computer games with intelligence , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[4]  Jennifer Ryan,et al.  A Two-Dimensional Genetic Algorithm for the Ising Problem , 1991, Complex Syst..

[5]  Mark. Deloura,et al.  Game Programming Gems , 2000 .

[6]  Bernd Freisleben.  A neural network that learns to play five-in-a-row , 1995, Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[7]  Byung Ro Moon,et al.  On Multi-Dimensional Encoding/Crossover , 1995, ICGA.

[8]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[9]  Sung Hoon Jung,et al.  Exploiting Intelligence in Fighting Action Games Using Neural Networks , 2006, IEICE Trans. Inf. Syst..

[10]  Sung Hoon Jung,et al.  Reinforcement Learning of Intelligent Characters in Fighting Action Games , 2006, ICEC.

[11]  Daniel Fu,et al.  Putting AI in Entertainment: An AI Authoring Tool for Simulation and Games , 2002, IEEE Intell. Syst..

[12]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[13]  Robert Fullér,et al.  Neural Fuzzy Systems , 1995 .

[14]  Rik Van de Walle,et al.  Multichannel distribution for universal multimedia access in home media gateways , 2006 .