We consider using machine learning techniques to help understand a large software system. In particular, we describe how learning techniques can be used to reconstruct abstract Da...
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...
Many real-world problems are inherently hierarchically structured. The use of this structure in an agent’s policy may well be the key to improved scalability and higher performa...