Titlebook: Learning for Decision and Control in Stochastic Networks; Longbo Huang Book 2023 The Editor(s) (if applicable) and The Author(s), under ex

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Network Optimization Techniques,d applied to network optimization. In this chapter, we review three important techniques that have been widely adopted, namely convex optimization, the drift method and the mean-field method. They are fundamental techniques that have found successful applications in many important areas. We will mai

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Learning Network Decisions,ed network control, and reinforcement learning (RL). The first two techniques focus more on algorithm design and analysis, whereas RL has both the theory aspect and data-driven aspect, in particular, deep reinforcement learning (DRL). Different from techniques presented in Chapter ., the methods pre

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Longbo HuangIntroduces Learning-Augmented Network Optimization based on a general stochastic network optimization model.Covers key theoretical tools for network research, as well as popular learning-based methods

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