Quasi Deterministic POMDPs and DecPOMDPs (Extended Abstract)
Camille Besse, Brahim Chaib-draa · 2010
In this paper, we study a particular subclass of partially observable models, called quasi-deterministic partially observable Markov decision processes (QDET-POMDPs), characterized by deterministic transitions and stochastic observations. While this framework does not model the same general problems as POMDPs, it still captures a number of interesting and challenging problems and have, in some cases, interesting properties. By studying the observability available in this subclass, we suggest that QDET-POMDPs may fall many steps in the complexity hierarchy. An extension of this framework to the decentralized case also reveals a subclass of numerous problems that can be approximated in polynomial space.