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A concise introduction to decentrali...

Oliehoek, Frans A.

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A concise introduction to decentralized POMDPs

Record Type:	Electronic resources : Monograph/item
Title/Author:	A concise introduction to decentralized POMDPs/ by Frans A. Oliehoek, Christopher Amato.
Author:	Oliehoek, Frans A.
other author:	Amato, Christopher.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xx, 134 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Decision making - Data processing. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-28929-8
ISBN:	9783319289298

A concise introduction to decentralized POMDPs
Oliehoek, Frans A.

A concise introduction to decentralized POMDPs[electronic resource] /by Frans A. Oliehoek, Christopher Amato. - Cham :Springer International Publishing :2016. - xx, 134 p. :ill., digital ;24 cm. - SpringerBriefs in intelligent systems, artificial intelligence, multiagent systems, and cognitive robotics,2196-548X. - SpringerBriefs in intelligent systems.Artificial intelligence, multiagent systems, and cognitive robotics..

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.

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.

ISBN: 9783319289298

Standard No.: 10.1007/978-3-319-28929-8doiSubjects--Topical Terms:

752376
Decision making
--Data processing.

LC Class. No.: T57.95

Dewey Class. No.: 658.4032

A concise introduction to decentralized POMDPs
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300 $a xx, 134 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in intelligent systems, artificial intelligence, multiagent systems, and cognitive robotics, $x 2196-548X
505 0 $a 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.
520 $a 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.
650 0 $a Decision making $x Data processing. $3 752376
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650 2 4 $a Control, Robotics, Mechatronics. $3 1002220
650 2 4 $a Optimization. $3 891104
700 1 $a Amato, Christopher. $3 2199694
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856 4 0 $u http://dx.doi.org/10.1007/978-3-319-28929-8
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