Using logic rules for concept refinement learning in first order logic

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Shi:2010:BIC-TA,

• author = "Zhenguo Shi and Zongtian Liu and Jianping Chen",
• title = "Using logic rules for concept refinement learning in first order logic",
• booktitle = "IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010",
• year = "2010",
• month = "23-26 " # sep,
• pages = "444--448",
• abstract = "In this paper, it has been explored that the use of logic rules as key element in concept refinement Learning. A logic rule is a formal grammar in logic for expressing formation rules of a formal language. First order logic in Inductive Logic Programming(ILP) and programming language in Genetic Programming(GP) are formal languages, the logic rule is available to express syntax and semantics of them. Concept refinement learning including inductive concept learning by employing ILP and evolutionary concept learning by employing GP. A framework is presented that combining ILP and GP using logic rules for concept refinement learning in first order logic. The viability of our approach is illustrated by comparing the performance of our learner with that of other concept learners such as Progol, CfgGP, GGP on a variety of target concepts. We conclude with some observations about the merits of our approach and about possible extensions.",
• keywords = "genetic algorithms, genetic programming, evolutionary concept learning, first order logic, formal grammar, formal language, formal languages, inductive concept refinement learning, inductive logic programming, logic rules, programming language, formal languages, grammars, inductive logic programming, learning by example, programming languages",
• DOI = "doi:10.1109/BICTA.2010.5645166",
• notes = "Also known as \cite{5645166}",

}

Genetic Programming entries for Zhenguo Shi Zongtian Liu Jianping Chen

Citations