A Concise Introduction to Decentralized POMDPs

1. Auflage 2016
ISBN: 978-3-319-28927-4
Verlag: Springer International Publishing

Buch, Englisch, 134 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 2467 g

Reihe: SpringerBriefs in Intelligent Systems

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. 

Zielgruppe

Research

Autoren/Hrsg.

Amato, Christopher

Oliehoek, Frans A.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Operations Research

Inhaltsverzeichnis

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.