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 making: reinforcement learning, decision theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research.
SpringerBriefs in Intelligent Systems