Competition-Based Neural Networks with Robotic Applications

Nonfiction, Science & Nature, Technology, Robotics, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Competition-Based Neural Networks with Robotic Applications by Shuai Li, Long Jin, Springer Singapore
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Author: Shuai Li, Long Jin ISBN: 9789811049477
Publisher: Springer Singapore Publication: May 30, 2017
Imprint: Springer Language: English
Author: Shuai Li, Long Jin
ISBN: 9789811049477
Publisher: Springer Singapore
Publication: May 30, 2017
Imprint: Springer
Language: English

Focused on solving competition-based problems, this book designs, proposes, develops, analyzes and simulates various neural network models depicted in centralized and distributed manners. Specifically, it defines four different classes of centralized models for investigating the resultant competition in a group of multiple agents. With regard to distributed competition with limited communication among agents, the book presents the first distributed WTA (Winners Take All) protocol, which it subsequently extends to the distributed coordination control of multiple robots.

Illustrations, tables, and various simulative examples, as well as a healthy mix of plain and professional language, are used to explain the concepts and complex principles involved. Thus, the book provides readers in neurocomputing and robotics with a deeper understanding of the neural network approach to competition-based problem-solving, offers them an accessible introduction to modeling technology and the distributed coordination control of redundant robots, and equips them to use these technologies and approaches to solve concrete scientific and engineering problems.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Focused on solving competition-based problems, this book designs, proposes, develops, analyzes and simulates various neural network models depicted in centralized and distributed manners. Specifically, it defines four different classes of centralized models for investigating the resultant competition in a group of multiple agents. With regard to distributed competition with limited communication among agents, the book presents the first distributed WTA (Winners Take All) protocol, which it subsequently extends to the distributed coordination control of multiple robots.

Illustrations, tables, and various simulative examples, as well as a healthy mix of plain and professional language, are used to explain the concepts and complex principles involved. Thus, the book provides readers in neurocomputing and robotics with a deeper understanding of the neural network approach to competition-based problem-solving, offers them an accessible introduction to modeling technology and the distributed coordination control of redundant robots, and equips them to use these technologies and approaches to solve concrete scientific and engineering problems.

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