Character Animation in Two-Player Adversarial Games
The incorporation of randomness is critical for the believability and effectiveness of controllers for characters in competitive games. We present a fully automatic method for generating intelligent real-time controllers for characters in such a game. Our approach uses game theory to deal with the ramifications of the characters acting simultaneously, and generates controllers which employ both long-term planning and an intelligent use of randomness. Our results exhibit nuanced strategies based on unpredictability, such as feints and misdirection moves, which take into account and exploit the possible strategies of an adversary. The controllers are generated by examining the interaction between the rules of the game and the motions generated from a parametric motion graph. This involves solving a large-scale planning problem, so we also describe a new technique for scaling this process to higher dimensions.
character animation game theory algorithms optimal control