- author = "Ting Hu and Wolfgang Banzhaf and Gabriela Ochoa",
- title = "How Neutrality Shapes Evolution: Simplicity Bias and Search",
- booktitle = "Proceedings of the 2025 Genetic and Evolutionary Computation Conference",
- year = "2025",
- editor = "Aniko Ekart and Nelishia Pillay",
- pages = "1008--1016",
- address = "Malaga, Spain",
- series = "GECCO '25",
- month = "14-18 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, fitness landscapes",
- isbn13 = "979-8-4007-1465-8",
-
URL = "
https://doi.org/10.1145/3712256.3726454",
-
DOI = "
doi:10.1145/3712256.3726454",
- size = "9 pages",
- abstract = "Neutrality, characterized by pathways in the genotype space that do not alter the phenotype or fitness, enables a broad exploration of evolutionary search. Simplicity bias describes the tendency of evolutionary systems to favor low-complexity solutions. This study investigates how neutrality contributes to simplicity bias in evolutionary systems using a Boolean Linear Genetic Programming framework. We introduce two fitness functions that use symmetry in solutions to promote neutrality, to analyze their effects on neutral network connectivity and search dynamics. Our results demonstrate that simpler phenotypes, characterized by lower Kolmogorov complexity, exhibit greater redundancy and connectivity, making them more accessible during neutral exploration. In addition, the proposed fitness functions significantly improve search success rates, especially for complex target phenotypes, by expanding neutral pathways. These findings shed light on the role of neutrality in shaping simplicity bias and provide practical insights to improve the effectiveness of evolutionary algorithms.",
-
notes = "portals linking different fitness plateaus.
A Recombination of the 34th International Conference on Genetic Algorithms (ICGA) and the 30th Annual Genetic Programming Conference (GP)",
