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Fitness Landscape Analysis and Image Filter Evolution Using Functional-Level CGP

, and . Proceedings of the 10th European Conference on Genetic Programming, volume 4445 of Lecture Notes in Computer Science, page 311--320. Valencia, Spain, Springer, (11 - 13 April 2007)
DOI: doi:10.1007/978-3-540-71605-1_29

Abstract

This work analyses fitness landscapes for the image filter design problem approached using functional-level Cartesian Genetic Programming. Smoothness and ruggedness of fitness landscapes are investigated for five genetic operators. It is shown that the mutation operator and the single-point crossover operator generate the smoothest landscapes and thus they are useful for practical applications in this area. In contrast to the gate-level evolution, a destructive behaviour of a simple crossover operator has not been confirmed.

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