New Perspectives on Cartesian Genetic Programming: A Survey

Mark Kocherovsky, Henning Cui, Illya Bakurov, Michael Heider, Roman Kalkreuth, Wolfgang Banzhaf

Abstract: Over the past twenty-five years, certain practices and assumptions in Cartesian Genetic Programming (CGP) have become conventional wisdom, yet recent research challenges their validity. This position paper critically examines these long-standing beliefs and proposes evidence-based alternatives for the CGP community. We address four misconceptions: The purported ineffectiveness of crossover operators; the overlooked impact of positional bias; problems with tournament selection on Boolean benchmarks; and the limitations of single-domain analysis. Through a review of recent literature, we identify a key principle underlying successful CGP operators—the preservation of node structural integrity during genetic operations. We discuss current best practices including rigorous hyperparameter tuning, cross-domain benchmarking, node-preserving operators, and modern fitness function design. Our analysis reveals that many accepted CGP practices, including the ubiquitous (1 + 4) evolution strategy, lack generalizability across problem domains. We believe that by reconsidering these assumptions and adopting the recommendations presented here, researchers and practitioners can develop more effective and robust CGP implementations.

External IDs:doi:10.1007/978-3-032-23005-8_6