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.
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Jadual kandungan
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.Beli ebook ini dan dapatkan 1 lagi PERCUMA!
Bahasa Inggeris ● Format PDF ● Halaman-halaman 134 ● ISBN 9783319289298 ● Saiz fail 2.5 MB ● Penerbit Springer International Publishing ● Bandar raya Cham ● Negara CH ● Diterbitkan 2016 ● Muat turun 24 bulan ● Mata wang EUR ● ID 4902070 ● Salin perlindungan Social DRM
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