Abstract. We present a major improvement to the dynamic programming (DP) algorithm for solving partially observable Markov decision processes (POMDPs).
A major improvement to the dynamic programming (DP) algorithm for solving partially observable Markov decision processes (POMDPs) is presented, showing that ...
Jul 11, 2012 · Abstract:We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes.
We present a major improvement to the incre- mental pruning algorithm for solving partially observable Markov decision processes. Our tech-.
Our technique targets the cross-sum step of the dynamic programming (DP) update, a key source of complexity in POMDP algorithms. Instead of reasoning about the ...
We describe an exact dynamic programming update for constrained partially observable Markov decision processes. (CPOMDPs). State-of-the-art exact solution of ...
We introduce point-based dynamic programming (DP) for decentralized partially observable Markov decision processes (DEC-POMDPs), a new discrete DP algo- rithm ...
ABSTRACT. Decentralized partially observable MDPs (DEC-POMDPs) provide a rich framework for modeling decision making by a team of agents.
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An approximate region-based value iteration (RBVI) algorithm is proposed to find the optimal policy for a partially observable Markov decision process ...
In this paper, we first discuss optimal dynamic programming and some approximate finite hori- zon DEC-POMDP algorithms. We then present a bounded dynamic ...
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