Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
413083 | Neurocomputing | 2006 | 29 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Mu-Chun Su, Chien-Hsing Chou, Eugene Lai, Jonathan Lee,