Behavior compilation for AI in games
Author(s)
Orkin, Jeffrey David; Smith, Tynan; Roy, Deb K.
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In order to cooperate effectively with human players, characters need to infer the tasks players are pursuing and select contextually appropriate responses. This process of parsing a serial input stream of observations to infer a hierarchical task structure is much like the process of compiling source code. We draw an analogy between compiling source code and compiling behavior, and propose modeling the cognitive system of a character as a compiler, which tokenizes observations and infers a hierarchical task structure. An evaluation comparing automatically compiled behavior to human annotation demonstrates the potential for this approach to enable AI characters to understand the behavior and infer the tasks of human partners.
Date issued
2010-10Department
Massachusetts Institute of Technology. Media LaboratoryJournal
Proceedings of the SixthAAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Citation
Orkin, Jeff, Tynan Smith, and Deb Roy. "Behavior compilation for AI in games." Sixth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (October 2010).
Version: Author's final manuscript