Exploitation Of Linkage Learning In Evolutionary Algorithms

Ed. By Ying-Ping Chen; Chen, Ying-Ping

ISBN 10: 3642128335 / ISBN 13: 9783642128332

Published by Springer, Berlin, 2010

About this Item

265 pages. 9.50x6.50x0.75 inches. In Stock.

Seller Inventory # x-3642128335

Bibliographic Details

• Title: Exploitation Of Linkage Learning In Evolutionary Algorithms
• Publisher: Springer, Berlin
• Publication Date: 2010
• Language: English
• ISBN 10: 3642128335
• ISBN 13: 9783642128332
• Binding: Hardcover
• Condition: Brand New
• Weight: 0.5 kilograms

About this title

Synopsis

One major branch of enhancing the performance of evolutionary algorithms is the exploitation of linkage learning. This monograph aims to capture the recent progress of linkage learning, by compiling a series of focused technical chapters to keep abreast of the developments and trends in the area of linkage. In evolutionary algorithms, linkage models the relation between decision variables with the genetic linkage observed in biological systems, and linkage learning connects computational optimization methodologies and natural evolution mechanisms. Exploitation of linkage learning can enable us to design better evolutionary algorithms as well as to potentially gain insight into biological systems. Linkage learning has the potential to become one of the dominant aspects of evolutionary algorithms; research in this area can potentially yield promising results in addressing the scalability issues.