Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7696
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wong Man Leung | en_US |
dc.contributor.author | Prof. LEUNG Kwong Sak | en_US |
dc.date.accessioned | 2023-03-30T05:35:42Z | - |
dc.date.available | 2023-03-30T05:35:42Z | - |
dc.date.issued | 1995 | - |
dc.identifier.citation | Proceedings of the IEEE Conference on Evolutionary Computation, 1995, vol. 2, pp. 733 - 736 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/7696 | - |
dc.description.abstract | Genetic 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.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartof | Proceedings of the IEEE Conference on Evolutionary Computation | en_US |
dc.title | Combining genetic programming and inductive logic programming using logic grammars | en_US |
dc.type | Conference Proceedings | en_US |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Applied Data Science | - |
Appears in Collections: | Applied Data Science - Publication |
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