Opening the Black Box: Alternative Search Drivers for Genetic Programming and Test-based Problems

dc.contributor.authorKrawiec, Krzysztof
dc.coverage.issue1cs
dc.coverage.volume23cs
dc.date.accessioned2019-06-26T10:18:07Z
dc.date.available2019-06-26T10:18:07Z
dc.date.issued2017-06-01cs
dc.description.abstractTest-based problems are search and optimization problems in which candidate solutions interact with multiple tests (examples, fitness cases, environments) in order to be evaluated. The approach conventionally adopted in most search and optimization algorithms involves aggregating the interaction outcomes into a scalar objective. However, passing different tests may require unrelated `skills' that candidate solutions may vary on.Scalar tness is inherently incapable of capturing such di erences and leaves a search algorithm largely uninformed about the diverse qualities of individual candidate solutions. In this paper, we discuss the implications of this fact and present a range of methods that avoid scalarization by turning the outcomes of interactions between programs and tests into 'search drivers' - partial, heuristic, transient pseudo-objectives that form multifaceted characterizations of candidate solutions. We demonstrate the feasibility of this approach by reviewing the experimental evidence from past work, confront it with related research endeavors, and embed it into a broader context of behavioral program synthesis.en
dc.formattextcs
dc.format.extent1-6cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2017 vol. 23, č. 1, s. 1-6. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2017.1.001en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/179191
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/41cs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0en
dc.subjectEvolutionary computationen
dc.subjecttest-based problemsen
dc.subjectgenetic programmingen
dc.subjectsearch driversen
dc.subjectcoevolutionary algorithmsen
dc.subjectsurrogate fitnessen
dc.titleOpening the Black Box: Alternative Search Drivers for Genetic Programming and Test-based Problemsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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