- author = "William {La Cava} and Lee Spector and Kourosh Danai",
- title = "Epsilon-lexicase Selection for Regression",
- booktitle = "GECCO '16: Proceedings of the 2016 Annual Conference on Genetic and Evolutionary Computation",
- year = "2016",
- editor = "Tobias Friedrich",
- pages = "741--748",
- keywords = "genetic algorithms, genetic programming",
- month = "20-24 " # jul,
- organisation = "SIGEVO",
- address = "Denver, USA",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- isbn13 = "978-1-4503-4206-3",
-
URL = "
https://arxiv.org/abs/1905.13266",
-
DOI = "
doi:10.1145/2908812.2908898",
- abstract = "Lexicase selection is a parent selection method that considers test cases separately, rather than in aggregate, when performing parent selection. It performs well in discrete error spaces but not on the continuous-valued problems that compose most system identification tasks. In this paper, we develop a new form of lexicase selection for symbolic regression, named epsilon-lexicase selection, that redefines the pass condition for individuals on each test case in a more effective way. We run a series of experiments on real-world and synthetic problems with several treatments of epsilon and quantify how e affects parent selection and model performance. e-lexicase selection is shown to be effective for regression, producing better fit models compared to other techniques such as tournament selection and age-fitness Pareto optimization. We demonstrate that epsilon can be adapted automatically for individual test cases based on the population performance distribution. Our experiments show that e-lexicase selection with automatic epsilon produces the most accurate models across tested problems with negligible computational overhead. We show that behavioural diversity is exceptionally high in lexicase selection treatments, and that e-lexicase selection makes use of more fitness cases when selecting parents than lexicase selection, which helps explain the performance improvement.",
-
notes = "http://www.williamlacava.com/research/lexicase
https://arxiv.org/abs/1905.13266 says 'Presented at GECCO-2016. Includes correction'
University of Massachusetts Amherst, Hampshire College
GECCO-2016 A Recombination of the 25th International Conference on Genetic Algorithms (ICGA-2016) and the 21st Annual Genetic Programming Conference (GP-2016)",
