A Concise Introduction to Decentralized POMDPs
Description
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.
Keywords
ComputersArtificial IntelligenceTechnology & EngineeringElectricalMathematicsOptimizationAutomationInformation Technology
2016Book
Author(s)Frans A. A. Oliehoek, Christopher Amato
PublisherSpringer International Publishing
ISBN9783319289274
LanguageEnglish
