Node Preservation and its Effect on Crossover in Cartesian Genetic Programming

📝 Original Info

• Title: Node Preservation and its Effect on Crossover in Cartesian Genetic Programming
• ArXiv ID: 2511.00634
• Date: 2025-11-01
• Authors: ** - 논문에 명시된 저자 정보가 제공되지 않았습니다. (원문 혹은 학술 데이터베이스에서 확인 필요) **

📝 Abstract

While crossover is a critical and often indispensable component in other forms of Genetic Programming, such as Linear- and Tree-based, it has consistently been claimed that it deteriorates search performance in CGP. As a result, a mutation-alone $(1+λ)$ evolutionary strategy has become the canonical approach for CGP. Although several operators have been developed that demonstrate an increased performance over the canonical method, a general solution to the problem is still lacking. In this paper, we compare basic crossover methods, namely one-point and uniform, to variants in which nodes are ``preserved,'' including the subgraph crossover developed by Roman Kalkreuth, the difference being that when ``node preservation'' is active, crossover is not allowed to break apart instructions. We also compare a node mutation operator to the traditional point mutation; the former simply replaces an entire node with a new one. We find that node preservation in both mutation and crossover improves search using symbolic regression benchmark problems, moving the field towards a general solution to CGP crossover.

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