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Constructing Game Agents from Video of Human Behavior

By Nan Li, David J. Stracuzzi, Gary Cleveland, Tolga Könik, Dan Shapiro, Matthew Molineaux, David Aha and Kamal Ali


Developing computer game agents is often a lengthy and expensive undertaking. Detailed domain knowledge and decision-making procedures must be encoded into the agent to achieve realistic behavior. In this paper, we simplify this process by using the ICARUS cognitive architecture to construct game agents. The system acquires structured, high fidelity methods for agents that utilize a vocabulary of concepts familiar to game experts. We demonstrate our approach by first acquiring behaviors for football agents from video footage of college football games, and then applying the agents in a football simulator

Year: 2009
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