A Concise Introduction to Decentralized POMDPs
Published on 14. June 2016
Book
Paperback/Softback
XX, 134 pages
978-3-319-28927-4 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2016
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
14 s/w Abbildungen, 22 farbige Abbildungen
XX, 134 p. 36 illus., 22 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 9 mm
Weight
248 gr
ISBN-13
978-3-319-28927-4 (9783319289274)
DOI
10.1007/978-3-319-28929-8
Schweitzer Classification
Other editions
Additional editions
Frans A. Oliehoek | Christopher Amato
A Concise Introduction to Decentralized POMDPs
E-Book
06/2016
Springer
€85.59
Available for download
Content
Multiagent Systems Under Uncertainty.- The Decentralized POMDP Framework.- Finite-Horizon Dec-POMDPs.- Exact Finite-Horizon Planning Methods.- Approximate and Heuristic Finite-Horizon Planning Methods.- Infinite-Horizon Dec-POMDPs.- Infinite-Horizon Planning Methods: Discounted Cumulative Reward.- Infinite-Horizon Planning Methods: Average Reward.- Further Topics.