SpringerBriefs in Intelligent Systems

1 total work

A Concise Introduction to Decentralized POMDPs

by Frans A. Oliehoek and Christopher Amato

Published 14 June 2016

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.