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Learning for Decision and Control in Stochastic Networks

Produktform: Buch / Einband - flex.(Paperback)

This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research. The authors present the topic based on a general stochastic network optimization model, and review several important theoretical tools that are widely adopted in network research, including convex optimization, the drift method, and mean-field analysis. The book then covers several popular learning-based methods, i.e., learning-augmented drift, multi-armed bandit and reinforcement learning, along with applications in networks where the techniques have been successfully applied. The authors also provide a discussion on potential future directions and challenges.weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Sprache(n): Englisch

ISBN: 978-3-031-31599-2 / 978-3031315992 / 9783031315992

Verlag: Springer International Publishing

Erscheinungsdatum: 21.06.2024

Seiten: 71

Auflage: 1

Autor(en): Longbo Huang

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