We present an approach to genetic programming difficulty based on a statistical study of program fitness landscapes. We use fitness distance correlation as an indicator of problem hardness and we empirically show that such a statistic is adequate in nearly all cases studied here. However, fitness distance correlation has some known problems that we also investigate by constructing an artificial landscape for which the correlation gives contradictory indications. Although our results confirm the usefulness of fitness distance correlation, we point out its shortcomings and give some hints for improvement in assessing problem hardness in genetic programming.
Tomassini, M., Vanneschi, L., Collard, P., Clergue, M. (2005). A study of fitness distance correlation as a difficulty measure in genetic programming. EVOLUTIONARY COMPUTATION, 13(2), 213-239 [10.1162/1063656054088549].
A study of fitness distance correlation as a difficulty measure in genetic programming
VANNESCHI, LEONARDO;
2005
Abstract
We present an approach to genetic programming difficulty based on a statistical study of program fitness landscapes. We use fitness distance correlation as an indicator of problem hardness and we empirically show that such a statistic is adequate in nearly all cases studied here. However, fitness distance correlation has some known problems that we also investigate by constructing an artificial landscape for which the correlation gives contradictory indications. Although our results confirm the usefulness of fitness distance correlation, we point out its shortcomings and give some hints for improvement in assessing problem hardness in genetic programming.
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