A Concise Introduction to Decentralized POMDPs (Paperback, 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Intelligent Systems
Release date:	June 2016
First published:	2016
Authors:	Frans A. Oliehoek • Christopher Amato
Dimensions:	235 x 155 x 13mm (L x W x T)
Format:	Paperback
Pages:	134
Edition:	1st ed. 2016
ISBN-13:	978-3-319-28927-4
Categories:	Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN:	3-319-28927-6
Barcode:	9783319289274

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