The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
— We introduce the Oracular Partially Observable Markov Decision Process (OPOMDP), a type of POMDP in which the world produces no observations; instead there is an “oracle,” ...
Abstract. One of the reasons for attending to agent technology is the evergrowing complexity of information systems and the increasing difficulty to foresee and plan for all potent...
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
Multiparty collaborative applications in which groups of people act in concert to achieve some real-world goal abound. In these situations, it is useful for a central planning age...