Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute a generic and expressive framework for multiagent planning under uncertainty. However, plannin...
Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J....
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
We present a logic programming language which uses a four-valued bilattice as the underlying framework for semantics of programs. The two orderings of the bilattice reflect the c...
Bamshad Mobasher, Jacek Leszczylowski, Don Pigozzi
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
The growing presence of household robots in inhabited environments arises the need for new robot task planning techniques. These techniques should take into consideration not only...
Marcello Cirillo, Lars Karlsson, Alessandro Saffio...