Title :
A study on Genetic Programming with layered learning and incremental sampling
Author :
Hien, Nguyen Thi ; Hoai, Nguyen Xuan ; McKay, Bob
Author_Institution :
Le Quy Don Univ., Hanoi, Vietnam
Abstract :
In this paper, we investigate the impact of a layered learning approach with incremental sampling on Genetic Programming (GP). The new system, called GPLL, is tested and compared with standard GP on twelve symbolic regression problems. While GPLL does not differ from standard GP on univariate target functions, it has better training efficiency on problems with bivariate targets. This indicates the potential usefulness of layered learning with incremental sampling in improving the efficiency of GP evolutionary learning.
Keywords :
genetic algorithms; learning (artificial intelligence); regression analysis; GP evolutionary learning; genetic programming; incremental sampling; layered learning; symbolic regression problem; univariate target function; Accuracy; Genetic programming; Machine learning; Robustness; Testing; Training; Training data;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949750
