This book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for the researcher and engineer who uses distributed optimization, game and learning theory in fields like dynamic economic dispatch, demand response management and PHEV routing of smart grids.
Distributed Optimization, Game and Learning Algorithms
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$298.00
Description
This book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for the researcher and engineer who uses distributed optimization, game and learning theory in fields like dynamic economic dispatch, demand response management and PHEV routing of smart grids.
This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges...
Describing a newoptimization algorithm, the "Teaching-Learning-Based Optimization (TLBO)," in aclear and lucid style, this book maximizes reader insights into how the TLBOalgorithm can be used to...
This book includes the papers presented at the Third International Workshop on Distributed Algorithms organized at La Colle-sur-Loup, near Nice, France, September 26-28, 1989 which followed the first...
This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike. Focusing on the natures and functions of agents,...
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