SpringerBriefs in Intelligent Systems

Oliehoek, Frans A.; Amato, Christopher

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. 

Details

Published by: Springer

Publication Date: 2016-06-14

Format: Paperback

ISBN-13: 9783319289274

DOI: 10.1007/978-3-319-28929-8

Dimensions: 235cm x155cm

Pages: 134