A Concise Introduction to Decentralized POMDPs

by Frans A. Oliehoek, Christopher Amato

Overview

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.

Product Details

ISBN-13:	9783319289274
Publisher:	Springer International Publishing
Publication date:	06/03/2016
Series:	SpringerBriefs in Intelligent Systems
Edition description:	1st ed. 2016
Pages:	134
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

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.