Research on artificial intelligence character based physics engine in 3d car game

Authors:
Jonghwa Choi;Dongkyoo Shin;Jinsung Choi;Dongil Shin
Affiliations:
Department of Computer Science and Engineering, Sejong University, Seoul, Korea;Department of Computer Science and Engineering, Sejong University, Seoul, Korea;Electronics and Telecommunications Research Institute, Taejun, Korea;Department of Computer Science and Engineering, Sejong University, Seoul, Korea
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

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Abstract

This paper deals with research on an intelligent game character that judges the game's physics situation and takes intelligent action in the game by applying a physics engine. The algorithm that recognizes the physics situation uses momentum back-propagation neural networks. In the experiment on physics situation recognition, a physics situation recognition algorithm where the number of input layers (number of physical parameters) and output layers (destruction value for the master car) is fixed has shown the best performance when the number of hidden layers is 3 and the learning count number is 30,000. Since we tested with rigid bodies only, we are currently studying efficient physics situation recognition for soft body objects.