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A Concise Introduction to Decentralized POMDPs
This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research.
154 pages, Kindle Edition
Published June 3, 2016
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