Multi-agent Optimization
Cetraro, Italy 2014
Published on 1. November 2018
VII, 310 pages
978-3-319-97142-1 (ISBN)
Description
This book contains three well-written research tutorials that inform the graduate reader about 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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
VII, 310 p. 28 illus., 22 illus. in color.
File size
6,94 MB
ISBN-13
978-3-319-97142-1 (9783319971421)
DOI
10.1007/978-3-319-97142-1
Schweitzer Classification
Other editions
Additional editions
Book
11/2018
Springer
€69.54
Shipment within 10-15 days
Content
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.
