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...
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 this paper, we present an integrated planning and robotic architecture that actively directs an agent engaged in an urban search and rescue (USAR) scenario. We describe three s...
Kartik Talamadupula, J. Benton, Paul W. Schermerho...
Case-based planning (CBP) systems are based on the idea of reusing past successful plans for solving new problems. Previous research has shown the ability of meta-reasoning approac...
Current efficient planners employ an informed search guided by a heuristic function that is quite expensive to compute. Thus, ordering nodes in the search tree becomes a key issue,...