Synthesis Lectures on Learning, Networks, and Algorithms

Huang, Longbo

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.

Details

Published by: Springer

Publication Date: 2024-06-21

Format: Paperback

ISBN-13: 9783031315992

DOI: 10.1007/978-3-031-31597-8

Dimensions: 240cm x168cm

Pages: 71