| 书目名称 | Exploitation of Linkage Learning in Evolutionary Algorithms |
| 编辑 | Ying-ping Chen |
| 视频video | |
| 概述 | The recent progress of linkage learning.Demonstrates a new connection between optimization methodologies and natural evolution mechanisms.Written by experts in the field |
| 丛书名称 | Adaptation, Learning, and Optimization |
| 图书封面 |  |
| 描述 | .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. . |
| 出版日期 | Book 2010 |
| 关键词 | Bayesian network; Evolutionary Computation; Linkage Learning; Markov; algorithm; algorithms; calculus; evol |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-642-12834-9 |
| isbn_softcover | 978-3-642-26327-9 |
| isbn_ebook | 978-3-642-12834-9Series ISSN 1867-4534 Series E-ISSN 1867-4542 |
| issn_series | 1867-4534 |
| copyright | Springer-Verlag Berlin Heidelberg 2010 |
发表于 2025-3-21 17:04:50
