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A concise introduction to decentrali...
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Amato, Christopher.
A concise introduction to decentralized POMDPs
Record Type:
Electronic resources : Monograph/item
Title/Author:
A concise introduction to decentralized POMDPsby 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.
Contained By:
Springer eBooks
Subject:
Decision makingData processing.
Online resource:
http://dx.doi.org/10.1007/978-3-319-28929-8
ISBN:
9783319289298$q(electronic bk.)
A concise introduction to decentralized POMDPs
Oliehoek, Frans A.
A concise introduction to decentralized POMDPs
[electronic resource] /by Frans A. Oliehoek, Christopher Amato. - Cham :Springer International Publishing :2016. - xx, 134 p. :ill., digital ;24 cm. - SpringerBriefs in intelligent systems, artificial intelligence, multiagent systems, and cognitive robotics,2196-548X. - SpringerBriefs in intelligent systems.Artificial intelligence, multiagent systems, and cognitive robotics..
Multiagent Systems Under Uncertainty -- The Decentralized POMDP Framework -- Finite-Horizon Dec-POMDPs -- Exact Finite-Horizon Planning Methods -- Approximate and Heuristic Finite-Horizon Planning Methods -- Infinite-Horizon Dec-POMDPs -- Infinite-Horizon Planning Methods: Discounted Cumulative Reward -- Infinite-Horizon Planning Methods: Average Reward -- Further Topics.
This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs) The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research.
ISBN: 9783319289298$q(electronic bk.)
Standard No.: 10.1007/978-3-319-28929-8doiSubjects--Topical Terms:
235779
Decision making
--Data processing.
LC Class. No.: T57.95
Dewey Class. No.: 658.4032
A concise introduction to decentralized POMDPs
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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.
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Computer Science (Springer-11645)
based on 0 review(s)
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http://dx.doi.org/10.1007/978-3-319-28929-8
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