Abstract
Game developers strive to have engaging believable characters in their work. One of the elements that has been pointed out as contributing to believability is social behavior. A category of social behavior is interpersonal conflict. In our current research we compare two AI approaches to model NPC conflict resolution strategies: one using the reactive planning language ABL and another using the AI framework FAtiMA. We identify the following metrics to evaluate social behavior modeling: mapping theory, emotion, model checking, variability, policy change. In our analysis we found it was easier to map conflict concepts in ABL and the model checking process was faster. FAtiMA had better support for emotion and other emergent attributes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
