Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
In this paper, we study strategies in incremental planning for ordering and grouping subproblems partitioned by the subgoals of a planning problem when each subproblem is solved b...
Abstract. Applying multi-agent systems in real world scenarios requires several essential research questions to be answered. Agents have to perceive their environment in order to t...
Frans C. A. Groen, Matthijs T. J. Spaan, Jelle R. ...
Currently, there is renewed interest in the problem, raised by Shafer in 1985, of updating probabilities when observations are incomplete (or setvalued). This is a fundamental pro...
POMDPs provide a rich framework for planning and control in partially observable domains. Recent new algorithms have greatly improved the scalability of POMDPs, to the point where...