UID:
almahu_9949984971402882
Umfang:
1 online resource (288 pages)
Ausgabe:
1st ed.
ISBN:
9780443216374
,
0443216371
Inhalt:
This book explores the field of distributed optimization and learning, focusing on multi-agent systems and their applications in various domains such as robotics, autonomous vehicles, and smart grids. It delves into fundamental concepts like consensus control, cooperative and competitive optimization, and game theory. The authors aim to provide a comprehensive understanding of distributed algorithms and their convergence, as well as their practical applications in networked systems. The book is intended for researchers and practitioners in control systems, electrical engineering, and related fields, offering insights into both theoretical foundations and real-world implementations.
Anmerkung:
Front Cover -- Distributed Optimization and Learning -- Copyright -- Contents -- Biography -- Preface -- I Fundamental concepts and algorithms -- 1 Introduction to distributed optimization and learning -- 1.1 Background -- 1.2 Literature review -- 1.2.1 Consensus control -- 1.2.2 Cooperative optimization -- 1.2.3 Competitive games -- 1.3 Book organization -- 2 Control perspective to single agent optimization -- 2.1 Unconstrained optimization -- 2.1.1 Convex function and convex optimization -- 2.1.2 Gradient descent algorithm -- 2.1.3 Convergence analysis -- 2.2 Set constrained optimization -- 2.3 Optimization with affine constraints -- 2.3.1 Algorithm and convergence analysis for affine constrained optimization -- 2.4 Discrete-time control perspective to optimization -- 2.4.1 Exact gradient descent algorithm and convergence -- 2.4.2 Stochastic optimization with approximated gradient -- 3 Distributed frameworks: Graphs, consensus, optimization, and learning -- 3.1 Centralized networks: Structures and limitations -- 3.2 Centralized optimization and learning -- 3.3 Graph theory -- 3.3.1 Laplacian matrix
Weitere Ausg.:
ISBN 9780443216367
Weitere Ausg.:
ISBN 0443216363
Sprache:
Englisch
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