Frans A. Oliehoek, Christopher Amato

A Concise Introduction to Decentralized POMDPs

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• SpringerBriefs in Intelligent Systems 0
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-28927-4
• 1st ed. 2016
• Seitenzahl: 156
• Erscheinungstermin: 14. Juni 2016
• Englisch
• Abmessung: 235mm x 155mm x 9mm
• Gewicht: 248g
• ISBN-13: 9783319289274
• ISBN-10: 3319289276
• Artikelnr.: 44247180

Inhaltsangabe

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.

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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.