Overview
- The first book to solve competition-based problems by means of various centralized or distributed neural network models
- Includes theoretical analyses, computer simulations, and robotic applications in neurocomputing fields
- Paves the way for the competition-based cooperative control of multiple redundant manipulators with limited communications
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
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Table of contents (6 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Competition-Based Neural Networks with Robotic Applications
Authors: Shuai Li, Long Jin
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-981-10-4947-7
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2018
Softcover ISBN: 978-981-10-4946-0Published: 08 June 2017
eBook ISBN: 978-981-10-4947-7Published: 30 May 2017
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: XV, 121
Number of Illustrations: 44 b/w illustrations
Topics: Computational Intelligence, Robotics and Automation, Artificial Intelligence, Mathematical Models of Cognitive Processes and Neural Networks