Abstract
In this paper, we show some experimental results of
tree-adjunct grammar guided genetic programming 6
(TAG3P) on the symbolic regression problem, a benchmark
problem in genetic programming. We compare the results
with genetic programming 9 (GP) and grammar guided
genetic programming 14 (GGGP). The results show that
TAG3P significantly outperforms GP and GGGP on the
target functions attempted in terms of probability of
success. Moreover, TAG3P still performed well when the
structural complexity of the target function was scaled
up.
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