Abstract
In Genetic Programming (GP), the fitness of individuals is normally computed by using a set of fitness cases (FCs). Research on the use of FCs in GP has primarily focused on how to reduce the size of these sets. However, often, only a small set of FCs is available and there is no need to reduce it. In this work, we are interested in using the whole FCs set, but rather than adopting the commonly used GP approach of presenting the entire set of FCs to the system from the beginning of the search, referred as static FCs, we allow the GP system to build it by aggregation over time, named as dynamic FCs, with the hope to make the search more amenable. Moreover, there is no study on the use of FCs in Dynamic Optimisation Problems (DOPs). To this end, we also use the Kendall Tau Distance (KTD) approach, which quantifies pairwise dissimilarities among two lists of fitness values. KTD aims to capture the degree of a change in DOPs and we use this to promote structural diversity. Results on eight symbolic regression functions indicate that both approaches are highly beneficial in GP.
E. Galván-López—Research conducted during Galván’s stay at TAU, INRIA and LRI, CNRS & U. Paris-Sud, Université Paris-Saclay, France.
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Notes
- 1.
50 independent runs, 2 types of replacement of individuals (arbitrary, Kendall tau distance-based), 3 types of changes, 8 problems.
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Acknowledgments
EGL would like to thank the TAU group at INRIA Saclay for hosting him during the outgoing phase of his Marie Curie fellowship and for financially supporting him to present this work at the conference. LT would like to thank CONACYT (project FC-2015-2:944) for providing partial funding.
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Galván-López, E., Vázquez-Mendoza, L., Schoenauer, M., Trujillo, L. (2018). On the Use of Dynamic GP Fitness Cases in Static and Dynamic Optimisation Problems. In: Lutton, E., Legrand, P., Parrend, P., Monmarché, N., Schoenauer, M. (eds) Artificial Evolution. EA 2017. Lecture Notes in Computer Science(), vol 10764. Springer, Cham. https://doi.org/10.1007/978-3-319-78133-4_6
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