Agents often have preference models that are more complicated than minimizing the expected execution cost. In this paper, we study how they should act in the presence of uncertaint...
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral 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...
View planning for three-dimensional (3D) reconstruction and inspection solves the problem of finding an efficient sequence of views allowing complete and high quality reconstructi...
Christoph Munkelt, Andreas Breitbarth, Gunther Not...
A generic architecture for autonomous agents is presented. In commonwith other current proposals the agent is capable of reacting to and reasoning about events which occur in its ...
Subrata Kumar Das, John Fox, D. Elsdon, Peter Hamm...