Autonomous search in constraint satisfaction via black hole: a performance evaluation using different choice functions

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dc.contributor.authorSoto, R.es_ES
dc.contributor.authorCrawford, B.es_ES
dc.contributor.authorOlivares, R.es_ES
dc.contributor.authorNiklander, S.es_ES
dc.contributor.authorOlguín, E.es_ES
dc.date.accessioned6/22/2022 13:33
dc.date.accessioned2022-09-30T16:31:50Z
dc.date.available6/22/2022 13:33
dc.date.available2022-09-30T16:31:50Z
dc.date.issued2016
dc.description.abstractAutonomous Search is a modern technique aimed at introducing self-adjusting features to problem-solvers. In the context of constraint satisfaction, the idea is to let the solver engine to autonomously replace its solving strategies by more promising ones when poor performances are identified. The replacement is controlled by a choice function, which takes decisions based on information collected during solving time. However, the design of choice functions can be done in very different ways, leading of course to very different resolution processes. In this paper, we present a performance evaluation of 16 rigorously designed choice functions. Our goal is to provide new and interesting knowledge about the behavior of such functions in autonomous search architectures. To this end, we employ a set of well-known benchmarks that share general features that may be present on most constraint satisfaction and optimization problems. We believe this information will be useful in order to design better autonomous search systems for constraint satisfaction. © Springer International Publishing Switzerland 2016.es_ES
dc.formatapplication/pdfes_ES
dc.identifier.doi10.1007/978-3-319-41000-5_6es_ES
dc.identifier.urihttps://doi.org/10.1007/978-3-319-41000-5_6
dc.language.isoenges_ES
dc.publisherSpringer Verlages_ES
dc.rightsinfo:eu-repo/semantics/closedAccesses_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es_ES
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)es_ES
dc.subjectComputer Sciencees_ES
dc.subjectMathematicses_ES
dc.subject.ocdehttp://purl.org/pe-repo/ocde/ford#1.02.01es_ES
dc.titleAutonomous search in constraint satisfaction via black hole: a performance evaluation using different choice functionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
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