Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
There has been substantial progress with formal models for sequential decision making by individual agents using the Markov decision process (MDP). However, similar treatment of m...
Raphen Becker, Shlomo Zilberstein, Victor R. Lesse...
The POMDP is considered as a powerful model for planning under uncertainty. However, it is usually impractical to employ a POMDP with exact parameters to model precisely the real-...
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
— We consider decision making in a Markovian setup where the reward parameters are not known in advance. Our performance criterion is the gap between the performance of the best ...