کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
413083 | 679723 | 2006 | 29 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A new approach to fuzzy classifier systems and its application in self-generating neuro-fuzzy systems
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
A classifier system is a machine learning system that learns syntactically simple string rules (called classifiers) through a genetic algorithm to guide its performance in an arbitrary environment. In a classifier system, the bucket brigade algorithm is used to solve the problem of credit assignment, which is a critical problem in the field of reinforcement learning. In this paper, we propose a new approach to fuzzy classifier systems and a neuro-fuzzy system referred to as ACSNFIS to implement the proposed fuzzy classifier system. The proposed system is tested by the balancing problem of a cart pole and the back-driving problem of a truck to demonstrate its performance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 69, Issues 4–6, January 2006, Pages 586–614
Journal: Neurocomputing - Volume 69, Issues 4–6, January 2006, Pages 586–614
نویسندگان
Mu-Chun Su, Chien-Hsing Chou, Eugene Lai, Jonathan Lee,