Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. We describe a novel BDI exe...
A helicopter agent has to plan trajectories to track multiple ground targets from the air. The agent has partial information of each target's pose, and must reason about its u...
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
In our experiments with four well-known systems for solving partially observable planning problems (Contingent-FF, MBP, PKS, and POND), we were greatly surprised to find that they...
Ronald Alford, Ugur Kuter, Dana S. Nau, Elnatan Re...