The use of an analytic quotient operator in genetic programming

Ni, Ji, Drieberg, Russ H. and Rockett, Peter I. (2013) The use of an analytic quotient operator in genetic programming. IEEE Transactions on Evolutionary Computation, 17 (1). pp. 146-152. ISSN 1089-778X

Full content URL: http://dx.doi.org/10.1109/TEVC.2012.2195319

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The Use of an Analytic Quotient Operator in Genetic Programming

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Abstract

We propose replacing the division operator used in genetic programming with an analytic quotient operator.We demonstrate that this analytic quotient operator systematically yields lower mean squared errors over a range of regression tasks, due principally to removing the discontinuities or singularities that can often result from using either protected or unprotected division. Further, the analytic quotient operator is differentiable. We also show that the new analytic quotient operator stabilizes the variance of the intermediate quantities in the tree.

Keywords:Genetic Programming, variance stabilization
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G760 Machine Learning
Divisions:College of Science > School of Computer Science
ID Code:15361
Deposited On:22 Oct 2015 10:11

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