Random subsampling improves performance in lexicase selection
Authors:
Open Access
- 13 July 2019
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 2028-2031
Abstract
No abstract availableFunding Information
- National Science Foundation (DGE-1424871,DBI-0939454,DEB-165571)
This publication has 10 references indexed in Scilit:
- Ecological theory provides insights about evolutionary computationPeerJ Preprints, 2018
- Relaxations of Lexicase Parent Selection2018
- A comparison of fitness-case sampling methods for genetic programmingJournal of Experimental & Theoretical Artificial Intelligence, 2017
- Sampling Methods in Genetic Programming Learners from Large Datasets: A Comparative Study2016
- Effects of Lexicase and Tournament Selection on Diversity Recovery and Maintenance2016
- General Program Synthesis Benchmark Suite2015
- Solving Uncompromising Problems With Lexicase SelectionIEEE Transactions on Evolutionary Computation, 2014
- Assessment of problem modality by differential performance of lexicase selection in genetic programming2012
- Random Sampling Technique for Overfitting Control in Genetic Programming2012
- ISOLATION BY DISTANCEGenetics, 1943