Plan recognition techniques frequently make rigid assumptions about the student's plans, and invest substantial effort to infer unobservable properties of the student. The pe...
Abstract. This paper presents an argumentation mechanism for reconciling conflicts between planning agents related to plan proposals, which are caused by inconsistencies between b...
Alexandros Belesiotis, Michael Rovatsos, Iyad Rahw...
Autonomous systems operating in real-world environments must be able to plan, schedule, and execute missions while robustly adapting to uncertainty and disturbances. Previous work...
Julie A. Shah, John Stedl, Brian C. Williams, Paul...
In this paper, we introduce a new heuristic search algorithm based on mean values for anytime planning, called MHSP. It consists in associating the principles of UCT, a bandit-base...
We present a decision making algorithm for agents that act in partially observable domains which they do not know fully. Making intelligent choices in such domains is very difficu...