This new model can give a more reliable optimal solution to cover the true parameters than the MAP model. It degenerates to the MAP model when prior information ...
This new model can give a more reliable optimal solution to cover the true parameters than the MAP model. It degenerates to the MAP model when prior information ...
Abstract—We study finite-state, finite-action, discounted infinite-horizon Markov decision processes with uncertain cor- related transition matrices in ...
Belief function model for reliable optimal set estimation of transition matrices in discounted infinite-horizon Markov decision processes. Article. Jul 2011.
This paper examines Markovian decision processes in which the transition probabilities corresponding to alternative decisions are not known with certainty.
Belief function model for reliable optimal set estimation of transition matrices in discounted infinite-horizon Markov decision processes · Efficient ...
As far as estimation is concerned, the main difference between the static and dynamic logit models is the interpretation of the v o function: in the static ...
The most commonly used formal model of fully-observable sequential decision processes is the Markov decision process (MDP) model. An MDP can be viewed as an ...
Partially observable Markov decision processes (POMDPs) provide an elegant math- ematical framework for modeling complex decision and planning problems in ...
Oct 25, 2022 · Finite model approximations for partially observed markov decision processes with discounted cost. IEEE Transactions on Automatic Control ...
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