Negative Slope Coefficient: A Measure to Characterize Genetic Programming Fitness Landscapes

Abstract

Negative slope coefficient has been recently introduced and empirically proven a suitable hardness indicator for some well known genetic programming benchmarks, such as the even parity problem, the binomial-3 and the artificial ant on the Santa Fe trail. Nevertheless, the original definition of this measure contains several limitations. This paper points out some of those limitations, presents a new and more relevant definition of the negative slope coefficient and empirically shows the suitability of this new definition as a hardness measure for some genetic programming benchmarks, including the multiplexer, the intertwined spirals problem and the royal trees.

DOI: 10.1007/11729976_16

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Cite this paper

@inproceedings{Vanneschi2006NegativeSC, title={Negative Slope Coefficient: A Measure to Characterize Genetic Programming Fitness Landscapes}, author={Leonardo Vanneschi and Marco Tomassini and Philippe Collard and S{\'e}bastien V{\'e}rel}, booktitle={EuroGP}, year={2006} }