A Comprehensive Comparison of Lexicase-Based Selection Methods for Symbolic Regression Problems
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-56957-9_12
Reference44 articles.
1. Aenugu, S., Spector, L.: Lexicase selection in learning classifier systems. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 356–364. ACM (2019)
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3. Chen, S.H.: Genetic Algorithms and Genetic Programming in Computational Finance. Springer, New York (2012). https://doi.org/10.1007/978-1-4615-0835-9
4. De Melo, V.V., Vargas, D.V., Banzhaf, W.: Batch tournament selection for genetic programming: the quality of lexicase, the speed of tournament. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 994–1002. GECCO ’19, ACM (2019)
5. Ding, L., Boldi, R., Helmuth, T., Spector, L.: Going faster and hence further with lexicase selection. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 538–541. ACM (2022)
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