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Scaling Up Decentralized MDPs Through Heuristic Search Jilles S. Dibangoye Christopher Amato INRIA Computer Science and AI Laboratory
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Document Date: 2013-03-11 16:08:28


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MIT Press / Multiagent Systems / Distributed Sensor Networks / Goldman / S. J. Bradtke S. P. / Princeton University Press / John Wiley and Sons / Intel / BP / /

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Hungary / Canada / United Kingdom / Greece / /

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Campus Scientifique / Massachusetts Institute of Technology / /

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heuristic search / policy search algorithm / online bounds / generic algorithm / exhaustive variant algorithm / real-world applications / policy solution / search nodes / policy search / cooperative systems / Approximate solutions / Real-time heuristic search / /

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Mac OSX / /

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PENTAGON / Princeton University / Massachusetts Institute of Technology / MPS BLP / National Aeronautics and Space Administration / /

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Christopher Amato / Matthijs Spaan / Ai / S. Zilberstein / V / Morgan Kaufmann / T. R. Yee / V / Marek Petrik / Arnaud Doniec Universit / /

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General / /

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Markov / /

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New York / GOA / Massachusetts / /

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Journal of Artificial Intelligence Research / /

Technology

BLP algorithm / RAM / few algorithms / memory-bounded algorithms / Dec-POMDP algorithms / exhaustive variant algorithm / decentralized Markov policy search algorithm / IPG algorithms / IPG algorithm / MPS algorithm / 239 Massachusetts Institute of Technology / LRTA∗ algorithm / 5 Algorithm / /

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