Robust and efficient plan recognition for dynamic multi-agent teams

8 years 4 months ago
Robust and efficient plan recognition for dynamic multi-agent teams
This paper addresses the problem of plan recognition for multiagent teams. Complex multi-agent tasks typically require dynamic teams where the team membership changes over time. Teams split into subteams to work in parallel, merge with other teams to tackle more demanding tasks, and disband when plans are completed. We introduce a new multi-agent plan representation that explicitly encodes dynamic team membership and demonstrate the suitability of this formalism for plan recognition. From our multi-agent plan representation, we extract local temporal dependencies that dramatically prune the hypothesis set of potentially-valid team plans. The reduced plan library can be efficiently processed to obtain the team state history. Naive pruning can be inadvisable when low-level observations are unreliable due to sensor noise and classification errors. In such conditions, we eschew pruning in favor of prioritization and show how our scheme can be extended to rank-order the hypotheses. Experim...
Gita Sukthankar, Katia P. Sycara
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where ATAL
Authors Gita Sukthankar, Katia P. Sycara
Comments (0)