Global Navigation of Assistant Robots using Partially Observable Markov Decision Processes

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The complexity of planning with partially-observable markov decision processes (2000).

Bayesian reinforcement learning for POMDP-based dialogue systems

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Probabilistic planning models and, in particular, Markov Decision Processes (MDPs), Partially Observable Markov Decision Processes (POMDPs) and Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs)

Partially Observable Markov Decision Processes (POMDPs)

Partially observable markov decision processes (pomdps).

Approximate planning with hierarchical partially observable Markov decision process models for robot navigation

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Global navigation of assistant robots using partially observable markov decision processes.

Systems—for example, hidden markov models (hmms), partially observable markov decision processes (pomdps), and transformed predictive state.