Behavior compilation for AI in games
Name
Behavior compilation.pdf
Size
246.43 KB
Format
Adobe PDF
Checksum (MD5)
3d8ef7cd2f5ca9ea107bfa68d1b7a0b4
Author(s)
Orkin, Jeffrey David
Smith, Tynan
Roy, Deb K.
Date Issued
October 2010
Journal
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
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.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://aaai.org/ocs/index.php/AIIDE/AIIDE10/paper/view/2115
