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.
Verel, S., Vanneschi, L., Tomassini, M., Collard, R. (2006). Negative slope coefficient: a measure to characterize genetic programming fitness landscapes. In Genetic Programming 9th European Conference, EuroGP 2006, Budapest, Hungary, April 10-12, 2006. Proceedings (pp.178-189). Springer [10.1007/11729976_16].
Negative slope coefficient: a measure to characterize genetic programming fitness landscapes
VANNESCHI, LEONARDO;
2006
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.
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