Arid
DOI10.2991/iske.2007.183
Improving on symbolic learning system based on genetic algorithm
Feng, Limei; Wang, Xizhao
通讯作者Feng, Limei
会议名称2007 International Conference on Intelligent Systems and Knowledge Engineering
会议日期OCT 15-16, 2007
会议地点Chengdu, PEOPLES R CHINA
英文摘要

This paper uses GAssist system to get symbolic rules and proposes four techniques to improve it. A new population initialization method is applied and fitness scaling is used to promote the population's convergence. It also improves on the deserted hierarchical selection operator and combines it with the MDL-based fitness function to control bloat effect. Finally, a new stop criterion to GA is studied. The experimental results show that the system is further improved. Comparing with other systems GA system is roughly comparable in generalization capacity but the efficiency needs improve.


英文关键词GAssist system population initialization method fitness scaling hierarchical selection operator MDL new stop criterion
来源出版物PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007)
ISSN1951-6851
出版年2007
ISBN978-90-78677-04-8
出版者ATLANTIS PRESS
类型Proceedings Paper
语种英语
国家Peoples R China
收录类别CPCI-S
WOS记录号WOS:000252560800184
WOS类目Computer Science, Artificial Intelligence
WOS研究方向Computer Science
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/296752
作者单位Hebei Univ, Machine Learning Ctr, Fac Math & Comp Sci, Baoding 071002, Peoples R China
推荐引用方式
GB/T 7714
Feng, Limei,Wang, Xizhao. Improving on symbolic learning system based on genetic algorithm[C]:ATLANTIS PRESS,2007.
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