Uncertain and complex environments demand that an agent be able to anticipate the actions of others in order to avoid resource conflicts with them and to realize its goals. Confli...
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
This paper addresses the problem of plan recognition for multi-agent teams. Complex multi-agent tasks typically require dynamic teams where the team membership changes over time. ...
Factored planning methods aim to exploit locality to efficiently solve large but "loosely coupled" planning problems by computing solutions locally and propagating limit...
Eric Fabre, Loig Jezequel, Patrik Haslum, Sylvie T...
Recently model checking representation and search techniques were shown to be efciently applicable to planning, in particular to non-deterministic planning. Such planning approach...