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cs.NE2026
Evaluation of Population Initialization Methods for Genetic Programming-based Symbolic Regression
Lukas Kammerer, Gabriel Kronberger, Deaglan J. Bartlett +3
We analyze the effect of optimizing the initial population of genetic programming (GP) for symbolic regression (SR) on the accuracy and complexity of solutions. We compare three we…
cs.NE2026
Guiding Multi-Objective Genetic Programming with Description Length Improves Symbolic Regression Solutions
Gabriel Kronberger, Fabricio Olivetti de Franca, Deaglan J. Bartlett +2
Symbolic regression with genetic programming (GPSR) may suffer from overfitting and structural bloat, especially when noise is present. In this paper we evaluate description length…