A Concise Introduction to Decentralized POMDPs
Springer International Publishing (Verlag)
978-3-319-28927-4 (ISBN)
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.
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.
| Erscheinungsdatum | 08.10.2016 |
|---|---|
| Reihe/Serie | SpringerBriefs in Intelligent Systems |
| Zusatzinfo | XX, 134 p. 36 illus., 22 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | Agents • artificial intelligence (incl. robotics) • Computer Science • Control, Robotics, Mechatronics • decentralized control • Dynamic Programming • Heuristics • Markov Decision Processes • Multiagent Planning • Multiagent Systems • Operations Research • Optimization • POMDPs • Reinforcement Learning • Search • Uncertainty |
| ISBN-10 | 3-319-28927-6 / 3319289276 |
| ISBN-13 | 978-3-319-28927-4 / 9783319289274 |
| Zustand | Neuware |
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