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Автор: Zhongguo Li, Zhengtao Ding
Издательство: Academic Press/Elsevier
Год: 2024
Страниц: 350
Язык: английский
Формат: epub
Размер: 24.0 MB
Distributed Optimization and Learning: A Control-Theoretic Perspective illustrates the underlying principles of distributed optimization and learning. The book presents a systematic and self-contained description of distributed optimization and learning algorithms from a control-theoretic perspective. It focuses on exploring control-theoretic approaches and how those approaches can be utilized to solve distributed optimization and learning problems over network-connected, multi-agent systems. As there are strong links between optimization and learning, this book provides a unified platform for understanding distributed optimization and learning algorithms for different purposes. For researchers, industrial practitioners, graduate students in optimization, control engineering, Data Sciences, Machine Learning, mechatronics, and applied mathematics, Mathematicians and engineers working on optimisation, learning and control systems, 3rd/4th-year undergraduate students with interests in multi-agent system optimization and control, robotics and Machine Learning.

