TY - GEN
T1 - A study on Genetic Programming with layered learning and incremental sampling
AU - Hien, Nguyen Thi
AU - Hoai, Nguyen Xuan
AU - McKay, Bob
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=80051974163&partnerID=8YFLogxK
U2 - 10.1109/CEC.2011.5949750
DO - 10.1109/CEC.2011.5949750
M3 - Conference contribution
SN - 9781424478347
T3 - 2011 IEEE Congress of Evolutionary Computation, CEC 2011
SP - 1179
EP - 1185
BT - 2011 IEEE Congress of Evolutionary Computation, CEC 2011
T2 - 2011 IEEE Congress of Evolutionary Computation, CEC 2011
Y2 - 5 June 2011 through 8 June 2011
ER -