Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/4289
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dc.contributor.authorRonoh, Nixon K.-
dc.contributor.authorMilgo, Edna-
dc.contributor.authorKiprop, Ambrose K.-
dc.contributor.authorManderick, Bernard-
dc.date.accessioned2021-03-11T06:26:03Z-
dc.date.available2021-03-11T06:26:03Z-
dc.date.issued2019-01-
dc.identifier.urihttp://ir.mu.ac.ke:8080/jspui/handle/123456789/4289-
dc.description.abstractIn this paper, we propose the use of schemata bandits for optimization. This technique is a subclass of hierarchical bandits where the bandits are schemata. We investigate its use on a benchmark of binary combinatorial optimization problems, the Maximum Satisfiability (MAXSAT) problem. We compare performance with hierarchical Bayesian Opti- mization Algorithms (hBOAs) namely GSAT and WALK- SAT. Results suggest that using a bandit strategy enhances solver performanceen_US
dc.language.isoenen_US
dc.publisherThe ACM Digital Libraryen_US
dc.subjectRandom searchen_US
dc.subjectSchemata banditsen_US
dc.subjectMAXSATen_US
dc.titleSchemata bandits for MAXSATen_US
dc.typeArticleen_US
Appears in Collections:School of Biological & Physical Sciences

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