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dc.contributor.authorSoto R.
dc.contributor.authorCrawford B.
dc.contributor.authorFlores J.
dc.contributor.authorMella F.
dc.contributor.authorGalleguillos C.
dc.contributor.authorJohnson F.
dc.contributor.authorParedes F.
dc.date.accessioned2020-09-02T22:28:40Z
dc.date.available2020-09-02T22:28:40Z
dc.date.issued2015
dc.identifier10.1007/978-3-319-20466-6_46
dc.identifier.citation9140, , 436-447
dc.identifier.issn03029743
dc.identifier.urihttps://hdl.handle.net/20.500.12728/6297
dc.descriptionConstraint Programing is a programming paradigm devoted to the efficient solving of constraint satisfaction problems (CSPs). A CSP is a formal problem representation mainly composed of variables and constraints defining relations among those variables. The resolution process of CSPs is commonly carried out by building and exploring a search tree that holds the possibles solutions. Such a tree is dynamically created by interleaving two different phases: enumeration and propagation. During enumeration, the variables and values are chosen to build the possible solution, while propagation intend to delete the values having no chance to reach a feasible result. Autonomous Search is a new technique that gives the ability to the resolution process to be adaptive by re-configuring its enumeration strategy when poor performances are detected. This technique has exhibited impressive results during the last years. However, such a re-configuration is hard to achieve as parameters are problem-dependent and their best configuration is not stable along the search. In this paper, we introduce an Autonomous Search framework that incorporates a new optimizer based on Cuckoo Search able to efficiently support the re-configuration phase. Our goal is to provide an automated, adaptive, and optimized search system for CSPs. We report encouraging results where our approach clearly improves the performance of previously reported Autonomous Search approaches for CSPs. © Springer International Publishing Switzerland 2015.
dc.language.isoen
dc.publisherSpringer Verlag
dc.sourceGelbukh A.Tan Y.Das S.Engelbrecht A.Buarque F.Shi Y.
dc.subjectAutonomous search
dc.subjectConstraint programming
dc.subjectCuckoo search
dc.subjectNature-inspired algorithms
dc.subjectSwarm-based optimization
dc.subjectArtificial intelligence
dc.subjectComputer programming
dc.subjectConstraint theory
dc.subjectForestry
dc.subjectOptimization
dc.subjectAutonomous searches
dc.subjectConstraint programming
dc.subjectCuckoo searches
dc.subjectDefining relations
dc.subjectNature inspired algorithms
dc.subjectProblem representation
dc.subjectProgramming paradigms
dc.subjectResolution process
dc.subjectConstraint satisfaction problems
dc.titleAutomated, adaptive, and optimized search for CSPs via cuckoo search
dc.typeConference Paper


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