Although a partially observable Markov decision process (POMDP) provides an appealing model for problems of planning under uncertainty, exact algorithms for POMDPs are intractable...
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
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-...