A Concise Introduction to Decentralized POMDPs: SpringerBriefs in Intelligent Systems
Autor Frans A. Oliehoek, Christopher Amatoen Limba Engleză Paperback – 14 iun 2016
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Specificații
ISBN-13: 9783319289274
ISBN-10: 3319289276
Pagini: 129
Ilustrații: XX, 134 p. 36 illus., 22 illus. in color.
Dimensiuni: 155 x 235 x 8 mm
Greutate: 0.23 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Intelligent Systems
Locul publicării:Cham, Switzerland
ISBN-10: 3319289276
Pagini: 129
Ilustrații: XX, 134 p. 36 illus., 22 illus. in color.
Dimensiuni: 155 x 235 x 8 mm
Greutate: 0.23 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Intelligent Systems
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
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.
Textul de pe ultima copertă
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.
Caracteristici
First book dedicated to this topic Suitable for researchers and graduate students in AI Assumes prior familiarity with agents, probability, and game theory Includes supplementary material: sn.pub/extras