TY  - BOOK
AU  - Wan,Hua
AU  - Yulu,Qi
AU  - Murai,Shunji
AU  - Huynh,Ngoc Phien
ED  - Canadian International Development Agency (CIDA),
TI  - Genetic classifier system approach in knowledge-based system
T2  - Thesis
PY  - 1993///
CY  - Bangkok
PB  - Asian Institute of Technology
KW  - Genetic algorithms
N1  - A thesis submitted in partial fulfillment of the requirement for the degree of Master of Science; Thesis (M.Sc.) - Asian Institute of Technology, 1993
N2  - To build up a knowledge-based system in Artificial Intelligence (Al), selecting an appropriate set of rules is one of the key problems. In this thesis, a Genetic Classifier System approach is employed to optimize the rules for knowledge-based system. The performance of a classifier system which belongs to the genetics-based machine learning architecture is tested using the various Genetic Algorithm operators, namely: reproduction, crossover, and mutation. Together with these GA operators, rule/message and apportionment of credit determine the fittest set of string rules, expressed as classifiers which serve as solution set, in two cases, namely: the eleven-multiplexer task and the Expert System of stock-cutting problem. Based on the experimental results, it is suggested that Genetic Classifier System is a feasible approach to optimize the rules for improving the performance of knowledge-based system
UR  - http://203.159.5.9/ait-thesis/detail.php?q=B16140
ER  -