Abstract
Multiagent plan recognition (MAPR) aims to recognize team structures and team behaviors from the observed team traces (action sequences) of a set of intelligent agents. This chapter introduces the problem formulation of MAPR based on partially observed team traces and presents a weighted MAX-SAT-based framework to recognize multiagent plans from partially observed team traces. This framework spans two approaches, MARS (MultiAgent plan Recognition System) and DARE (Domain model-based multiAgent REcognition), with respect to different input knowledge. MARS requires as input a plan library, while DARE requires as input a set of previously created action models. Both approaches highlight our novel computational framework for multiagent plan recognition.
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 callDisclaimer: 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.
