Lexi2: lexicase selection with lexicographic parsimony pressure: Lexicase selection with lexicographic parsimony pressure
Bloat, a well-known phenomenon in Evolutionary Computation,often slows down evolution and complicates the task of interpreting the results. We propose Lexi2, a new selection and bloat-control method, which extends the popular lexicase selection method, by including a tie-breaking step which considers attributes related to the size of the individuals. This new step applies lexicographic parsimony pressure during the selection process and is able to reduce the number of random choices performed by lexicase selection (which happen when more than a single individual correctly solve the selected training cases).
Furthermore, we propose a new Grammatical Evolution-specific,low-cost diversity metric based on the grammar mapping modulus operations remainders, which we then utilise with Lexi2.
We address four distinct problems, and the results show that Lexi2 is able to reduce significantly the length, the number of nodes and the depth for all problems, to maintain a high level of diversity in three of them, and to significantly improve the fitness score in two of them. In no case does it adversely impact the fitness.
Automatic Design of Digital Circuits (ADDC)
Science Foundation IrelandFind out more...
PublicationGECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference July 2022 Pages 929–937
PublisherAssociation for Computing Machinery
Other Funding informationThis publication has emanated from research conducted with the financial support of Science Foundation Ireland under Grant number 16/IA/4605. The third author is also financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES), Finance Code 001, and the Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ). Open Access funding provided by the IRel Consortium.
Department or School
- Computer Science & Information Systems