Competition-Based Neural Networks with Robotic Applications (Paperback, 1st ed. 2018)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	SpringerBriefs in Applied Sciences and Technology
Release date:	June 2017
First published:	2018
Authors:	Shuai Li • Long Jin
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	121
Edition:	1st ed. 2018
ISBN-13:	978-981-10-4946-0
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
LSN:	981-10-4946-7
Barcode:	9789811049460

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