Exploiting Belief Locality in Run-Time Decision-Theoretic Planners

Abstract

While Partially-Observable Markov Decision Processes have become a popular means of representing realistic planning problems, exact approaches to finding POMDP policies are extremely computationally complex. An alternative approach for control in POMDP domains is to use run-time optimization over action sequences in a dynamic decision network. While exact… (More)

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