We consider symbolic dynamic programming (SDP) for solving Markov Decision Processes (MDP) with factored state and action spaces, where both states and actions are described by se...
Aswin Raghavan, Saket Joshi, Alan Fern, Prasad Tad...
Decision making models for autonomous agents have received increased attention, particularly in the field of intelligent robots. In this paper we will show how a Defeasible Logic ...
In this paper we extend the Revision Programming framework--a logic-based framework to express and maintain constraints on knowledge bases-with different forms of preferences. Pref...
Most traditional approaches to probabilistic planning in relationally specified MDPs rely on grounding the problem w.r.t. specific domain instantiations, thereby incurring a com...
Combining probability and first-order logic has been the subject of intensive research during the last ten years. The most well-known formalisms combining probability and some sub...