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A concise introduction to decentralized POMDPs[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	658.4032
書名/作者:	A concise introduction to decentralized POMDPs/ by Frans A. Oliehoek, Christopher Amato.
作者:	Oliehoek, Frans A.
其他作者:	Amato, Christopher.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xx, 134 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Decision making - Data processing.
標題:	Multiagent systems.
標題:	Computer Science.
標題:	Artificial Intelligence (incl. Robotics)
標題:	Control, Robotics, Mechatronics.
標題:	Optimization.
ISBN:	9783319289298
ISBN:	9783319289274
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-28929-8

A concise introduction to decentralized POMDPs[electronic resource] /
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:

341470
Decision making
--Data processing.

LC Class. No.: T57.95

Dewey Class. No.: 658.4032

A concise introduction to decentralized POMDPs[electronic resource] /
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