Jeff Wu

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We give an optimal dynamic programming algorithm to solve a class of finite-horizon decentralized Markov decision processes (MDPs). We consider problems with a broadcast information structure that consists of a central node that only has access to its own state but can affect several outer nodes, while each outer node has access to both its own state and(More)
We present an exact dynamic programming solution for a finite-horizon decentralized two-player Markov decision process , where player 1 only has access to its own states, while player 2 has access to both player's states but cannot affect player 1's states. The solution is obtained by solving several centralized partially-observable Markov decision(More)
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