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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Introduction,been an active research field over the past decades, and many important results have been developed. Most notably, the seminal works (Tassiulas et al. .; Kelly .; Neely et al. .; Chiang et al. .), laid a solid foundation for the field. Building on their foundation, developments in many important aspects about network optimization have been made.

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Network Optimization Techniques,e drift method and the mean-field method. They are fundamental techniques that have found successful applications in many important areas. We will mainly focus their standard forms when used in network optimization.

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Longbo HuangSymposium was the "Theatersaal" of the Austrian Academy of Sciences. The Symposium was attended by 71 persons from 23 countries. In addition, several Austrian graduate students and research associates participated in the meeting. In the 5-day Symposium a total of 48 papers were presented. All of the

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Longbo Huangupports and free edges, in the vicinity of concentrated loads and at thickness jumps cannot be described in a sufficient way by 1D- and 2D-BVPs. In these disturbed subdomains dimensional (d)-adaptivity and model (m-)adaptivity have to be performed coupled with h- and/or p-adaptivity using hierarchic

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Longbo Huang, with a considerable health risk amount for the long-time period, and leading to a heavy environmental workplace. Vibrations can also cause damage to the machinery, misadjusting pieces and rising up maintenance costs. In order to correctly modeling these nonlinear systems we use the well-known Bouc

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Introduction,ower systems (Fig. . presents a general stochastic network). As a result, optimally controlling network operations, a.k.a., network optimization, has been an active research field over the past decades, and many important results have been developed. Most notably, the seminal works (Tassiulas et al.