Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7696
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dc.contributor.authorWong Man Leungen_US
dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.date.accessioned2023-03-30T05:35:42Z-
dc.date.available2023-03-30T05:35:42Z-
dc.date.issued1995-
dc.identifier.citationProceedings of the IEEE Conference on Evolutionary Computation, 1995, vol. 2, pp. 733 - 736en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7696-
dc.description.abstractGenetic Programming (GP) and Inductive Logic Programming (ILP) have received increasing interest recently. Since their formalisms are so different, these two approaches cannot be integrated easily though they share many common goals and functionalities. A unification will greatly enhance their problem solving power. In this paper, a framework to combine GP and ILP is presented. The framework is based on a formalism of logic grammars and a system called LOGENPRO (the LOgic grammar based GENetic PROgramming system) is developed. It is so flexible that programs in different programming languages such as LISP, Prolog, and C can be induced. The performance of LOGENPRO in inducing logic programs from noisy examples is also evaluated. A detailed comparison to FOIL and mFOIL has been conducted. The experiment demonstrates that LOGENPRO is a promising alternative to other inductive logic programming systems and sometimes is superior for handling noisy data.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofProceedings of the IEEE Conference on Evolutionary Computationen_US
dc.titleCombining genetic programming and inductive logic programming using logic grammarsen_US
dc.typeConference Proceedingsen_US
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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