Typically, autonomous believable agents are implemented using static, hand-authored reactive behaviors or scripts. This hand-authoring allows designers to craft expressive behavior for characters, but can lead to excessive authorial burden, as well as result in characters that are brittle to changing world dynamics. In this paper, we present an approach for the runtime adaptation of reactive behaviors for autonomous believable characters. Extending transformational planning, our system allows autonomous characters to monitor and reason about their behavior execution and to use this reasoning to dynamically rewrite their behaviors. In our evaluation, we transplant two characters in a sample tag game from the original world they were written for into a different one, resulting in behavior that violates the author intended personality. The reasoning layer successfully adapts the character's behaviors so as to bring its long-term behavior back into agreement with its personality.

Authors

• Peng Zang
• Manish Mehta College of Computing Georgia Institute of Technology Atlanta, GA 30332-0760
• Michael Mateas University of California, Santa Cruz
• Ashwin Ram

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