Title :
Inverse learning based on extension logic
Author :
He, Bin ; Chen, Xiao-Yin ; Gao, Jing-Guang
Author_Institution :
Dept. of Inf. Manage. Eng., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
Based on extension logic, this paper presents a novel formalized learning method, inverse learning, which are uniquely suitable for dealing with incompatible problems. Firstly, inverse matter-elements are introduced, inverse extension of matter-elements is discussed, and inverse extension of transformations is analyzed. And then the calculation of inverse degree is studied. Finally, the inverse reasoning is explored and relevant inverse reasoning rules are given. The study shows that inverse learning can be developed using inverse extensions and inverse reasoning.
Keywords :
formal logic; inference mechanisms; learning (artificial intelligence); extension logic; formalized learning method; incompatible problems; inverse degree calculation; inverse extension; inverse learning; inverse matter-elements; inverse reasoning; inverse transformation extension; Biomedical engineering; Educational institutions; Engineering management; Environmental economics; Health information management; Helium; Learning systems; Logic; Machine learning; Technology management; Extension logic; Inverse elements; Inverse extension; Inverse learning; Inverse reasoning; Transformation;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527464