Udvidet returret til d. 31. januar 2025

Learning for Decision and Control in Stochastic Networks

Bag om Learning for Decision and Control in Stochastic Networks

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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783031315961
  • Indbinding:
  • Hardback
  • Sideantal:
  • 84
  • Udgivet:
  • 20. juni 2023
  • Udgave:
  • 23001
  • Størrelse:
  • 173x11x246 mm.
  • Vægt:
  • 333 g.
  • BLACK NOVEMBER
Leveringstid: 8-11 hverdage
Forventet levering: 7. december 2024

Beskrivelse af Learning for Decision and Control in Stochastic Networks

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.

Brugerbedømmelser af Learning for Decision and Control in Stochastic Networks



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