Linkage in Evolutionary Computation 2007 EV |
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Call for Book Chapters Title: Linkage in Evolutionary Computation ISBN: 978-3-540-85067-0 Overview Genetic and evolutionary algorithms (GEAs) are powerful search methods based on the paradigm of evolution and widely applied to solve problems in many disciplines. In order to improve the performance and applicability, numerous sophisticated mechanisms have been introduced and integrated into GEAs in the past decades. One major category of these enhancing mechanisms is the concept of linkage, which models the relation between the decision variables with the genetic linkage observed in biological systems, and linkage learning techniques. Linkage learning connects the computational optimization methodologies and the natural evolution mechanisms. Not only can learning and adapting natural mechanisms enable us to design better computational methodologies, but also the insight gained by observing and analyzing the algorithmic behavior permits us to further understand biological systems, based on which GEAs are developed. Scope This edited volume aims at reviewing the state-of-art linkage learning techniques, exchanging ideas and viewpoints on linkage, as well as discussing the future research directions. We invite researchers to submit their original work related to, but not limited to, the following topics:
Submission Guidelines Manuscripts should be prepared according to the series book format provided by Springer, and the page limit for each chapter is 30 pages. Prospective authors are invited to submit a one to two-page proposal describing the topic of the chapter. The proposal should include the chapter organization, number of pages of the final manuscript and contact authors. Please direct all correspondences and proposal submissions to one of the editors. Important Dates Indication of Intention to Contribute: Submission of Manuscripts: Submission of Review Comments: Submission of Revised Manuscripts: Submission of the Final Camera-ready Manuscript (to Springer): Editors
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Last Updated on Tuesday, 15 December 2009 11:53 |