Angelia Nedic, Jong-Shi Pang, Gesualdo Scutari, Ying Sun

Multi-agent Optimization (eBook, PDF)

Cetraro, Italy 2014
Redaktion: Facchinei, Francisco; Pang, Jong-Shi

• Format: PDF

Produktbeschreibung

This book contains three well-written research tutorials that will allow the reader to easily get to the forefront of current research in multi-agent optimization. These tutorials cover topics that have not yet found their way in standard books and offer the reader the unique opportunity to be guided by major researchers in the respective fields. Multi-agent optimization, lying at the intersection of classical optimization, game theory, and variational inequality theory, is at the forefront of modern optimization and has recently undergone a dramatic development. It seems timely to provide an overview that describes in detail ongoing research and important trends. This book concentrates on Distributed Optimization over Networks; Differential Variational Inequalities; and Advanced Decomposition Algorithms for Multi-agent Systems. This book will appeal to both mathematicians and mathematically oriented engineers and will be the source of inspiration for PhD students and researchers.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 310
• Erscheinungstermin: 1. November 2018
• Englisch
• ISBN-13: 9783319971421
• Artikelnr.: 58521712

Inhaltsangabe

Preface.- Distributed Optimization over Networks by Angelia Nedich. - Five Lectures on Differential Variational Inequalities by Jong-Shi Pang. - Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization by Gesualdo Scutari and Ying Sun.