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Research explores recombination operators for improved Cartesian Genetic Programming

By PulseAugur Editorial · [2 sources] ·

A new research paper explores improvements in Cartesian Genetic Programming (CGP) by examining recombination-based operators. Traditionally, CGP has relied heavily on mutation, with recombination approaches often overlooked due to perceived performance limitations. This study investigates two specific recombination operators, subgraph crossover and discrete phenotypic recombination, using the SRBench platform for symbolic regression. The findings indicate that through hyperparameter optimization, recombination-based CGP can achieve enhanced performance. AI

IMPACT This research could lead to more efficient evolutionary algorithms for symbolic regression tasks.

RANK_REASON The cluster contains an academic paper detailing research findings on a specific AI technique.

Read on arXiv cs.NE (Neural & Evolutionary) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Research explores recombination operators for improved Cartesian Genetic Programming

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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Duy Long Tran, Anja Jankovic, Marie Anastacio, Holger Hoos, Roman Kalkreuth ·

    Improving Evaluation of Recombination-based Cartesian Genetic Programming

    arXiv:2605.28353v1 Announce Type: cross Abstract: Cartesian Genetic Programming has traditionally been using mutation as its main and often sole genetic operator to drive evolutionary search. Despite advancements in recent years, recombinationbased approaches have long been avoid…

  2. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Roman Kalkreuth ·

    Improving Evaluation of Recombination-based Cartesian Genetic Programming

    Cartesian Genetic Programming has traditionally been using mutation as its main and often sole genetic operator to drive evolutionary search. Despite advancements in recent years, recombinationbased approaches have long been avoided, due to apparent lack of performance gains. Thi…

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