A Concise Introduction to Decentralized POMDPs

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: re...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Oliehoek, Frans A. (Autor), Amato, Christopher (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:SpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,
Temas:
Artificial intelligence.
Control engineering.
Robotics.
Automation.
Mathematical optimization.
Artificial Intelligence.
Control, Robotics, Automation.
Optimization.
Acceso en línea:Texto Completo
Descripción
Sumario: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. .
Descripción Física:XX, 134 p. 36 illus., 22 illus. in color. online resource.
ISBN:9783319289298
ISSN:2196-5498

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