GSBAR learning algorithm based on genetic programming
Yongxian Wang · Journal of Tsinghua University(Science and Technology) · 2003
The general similarity-based approximate reasoning method (GSBAR) needs a learning algorithm to find its functional parameters based on various cases. This paper describes a GSBAR learning algorithm based on genetic programming. The definition of this algorithm, simplification of the learning task, main components, and steps were presented. An illustrative example shows that the GSBAR learning algorithm most likely finds the optimal result. The function searching ability of the GSBAR learning algorithm makes the GSBAR algorithm more adaptive to a variety of situations.