Linear Genetic Programming presents a variant of genetic
programming (GP) that evolves imperative computer programs as
linear sequences of instructions, in contrast to the more
traditional functional expressions or syntax trees. Primary
characteristics of linear program structure are exploited to
achieve acceleration of both execution time and evolutionary
progress. Online analysis and optimization of program code lead to
more efficient techniques and contribute to a better understanding
of the method and its parameters. In particular, the reduction of
structural variation step size and non-effective variations play a
key role in finding higher quality and less complex solutions.
Typical GP phenomena, such as non-effective code, neutral
variations, and code growth are investigated from the perspective
of linear GP. This book serves as a reference for researchers; it
also contains sufficient introductory material for students and
those who are new to the field.
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