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.
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