We develop a hierarchical approach to planning for partially observable Markov decision processes (POMDPs) in which a policy is represented as a hierarchical finite-state control...
We consider the average cost problem for partially observable Markov decision processes (POMDP) with finite state, observation, and control spaces. We prove that there exists an -...
Regarding nite state machines as Markov chains facilitates the application of probabilistic methods to very large logic synthesis and formal verication problems. Recently, we ha...
Gary D. Hachtel, Enrico Macii, Abelardo Pardo, Fab...
The unichain classification problem detects whether a finite state and action MDP is unichain under all deterministic policies. This problem is NP-hard [11]. This paper provides p...