Behavior Compilation for AI in Games

Authors

  • Jeff Orkin Massachusetts Institute of Technology
  • Tynan Smith Massachusetts Institute of Technology
  • Deb Roy Massachusetts Institute of Technology

Keywords:

Behavior modeling, Data Collection and Encoding, Planning, NPC Coordination

Abstract

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.

Downloads

Published

2010-10-10

How to Cite

Orkin, J., Smith, T., & Roy, D. (2010). Behavior Compilation for AI in Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 6(1), 162-167. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/12406