Subgoal interactions have received considerable attention in AI Planning. Earlier analyses by Korf [11] and Joslin and Roach [6] were done in terms of the topology of the space of...
Subbarao Kambhampati, Laurie H. Ihrig, Biplav Sriv...
Abstract. In recent years, within the planning literature there has been a departure from approaches computing total plans for given goals, in favour of approaches computing partia...
Paolo Mancarella, Fariba Sadri, Giacomo Terreni, F...
In our research we study rational agents which learn how to choose the best conditional, partial plan in any situation. The agent uses an incomplete symbolic inference engine, emp...
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
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...