DocumentCode
3229083
Title
Using logic rules for concept refinement learning in first order logic
Author
Shi, Zhenguo ; Liu, Zongtian ; Chen, Jianping
Author_Institution
Sch. of Comput. Sci. & Technol., Nantong Univ., Nantong, China
fYear
2010
fDate
23-26 Sept. 2010
Firstpage
444
Lastpage
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
formal languages; grammars; inductive logic programming; learning by example; programming languages; evolutionary concept learning; first order logic; formal grammar; formal language; formal languages; genetic programming; inductive concept refinement learning; inductive logic programming; logic rules; programming language; Genetics; evolutionary concept learning; genetic programming; inductive concept learning; inductive logic programming; logic rule; refinement concept learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-6437-1
Type
conf
DOI
10.1109/BICTA.2010.5645166
Filename
5645166
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