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Comparison of Semantic-aware Selection Methods in Genetic Programming

Published: 11 July 2015 Publication History

Abstract

This study investigates the performance of several semantic- aware selection methods for genetic programming (GP). In particular, we consider methods that do not rely on complete GP semantics (i.e., a tuple of outputs produced by a program for fitness cases (tests)), but on binary outcome vectors that only state whether a given test has been passed by a program or not. This allows us to relate to test-based problems commonly considered in the domain of coevolutionary algorithms and, in prospect, to address a wider range of practical problems, in particular the problems where desired program output is unknown (e.g., evolving GP controllers). The selection methods considered in the paper include implicit fitness sharing (ifs), discovery of derived objectives (doc), lexicase selection (lex), as well as a hybrid of the latter two. These techniques, together with a few variants, are experimentally compared to each other and to conventional GP on a battery of discrete benchmark problems. The outcomes indicate superior performance of lex and ifs, with some variants of doc showing certain potential.

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  • (2024)A survey on batch training in genetic programmingGenetic Programming and Evolvable Machines10.1007/s10710-024-09501-626:1Online publication date: 29-Nov-2024
  • (2023)Probabilistic Lexicase SelectionProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590375(1073-1081)Online publication date: 15-Jul-2023
  • (2022)Problem-Solving Benefits of Down-Sampled Lexicase SelectionArtificial Life10.1162/artl_a_0034127:3–4(183-203)Online publication date: 16-Mar-2022
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cover image ACM Conferences
GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation
July 2015
1568 pages
ISBN:9781450334884
DOI:10.1145/2739482
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 11 July 2015

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Author Tags

  1. genetic programming
  2. program semantics
  3. selection operators

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Cited By

View all
  • (2024)A survey on batch training in genetic programmingGenetic Programming and Evolvable Machines10.1007/s10710-024-09501-626:1Online publication date: 29-Nov-2024
  • (2023)Probabilistic Lexicase SelectionProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590375(1073-1081)Online publication date: 15-Jul-2023
  • (2022)Problem-Solving Benefits of Down-Sampled Lexicase SelectionArtificial Life10.1162/artl_a_0034127:3–4(183-203)Online publication date: 16-Mar-2022
  • (2022)Lexicase selection at scaleProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3520304.3534026(2054-2062)Online publication date: 9-Jul-2022
  • (2022)Going faster and hence further with lexicase selectionProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3520304.3529059(538-541)Online publication date: 9-Jul-2022
  • (2022)Population Diversity Leads to Short Running Times of Lexicase SelectionParallel Problem Solving from Nature – PPSN XVII10.1007/978-3-031-14721-0_34(485-498)Online publication date: 10-Sep-2022
  • (2021)Lexicase SelectionProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3449726.3461408(839-855)Online publication date: 8-Jul-2021
  • (2020)Genetic programming approaches to learning fair classifiersProceedings of the 2020 Genetic and Evolutionary Computation Conference10.1145/3377930.3390157(967-975)Online publication date: 25-Jun-2020
  • (2020)On the importance of specialists for lexicase selectionGenetic Programming and Evolvable Machines10.1007/s10710-020-09377-2Online publication date: 30-Jan-2020
  • (2019)Lexicase selection of specialistsProceedings of the Genetic and Evolutionary Computation Conference10.1145/3321707.3321875(1030-1038)Online publication date: 13-Jul-2019
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