Online program simplification in genetic programming

Authors:
Mengjie Zhang;Phillip Wong;Dongping Qian
Affiliations:
School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, Wellington, New Zealand;School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, Wellington, New Zealand;Artificial Intelligence Research Centre, Agricultural University of Hebei, China
Venue:
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Year:
2006

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Abstract

This paper describes an approach to online simplification of evolved programs in genetic programming (GP). Rather than manually simplifying genetic programs after evolution for interpretation purposes only, this approach automatically simplifies programs during evolution. In this approach, algebraic simplification rules, algebraic equivalence and prime techniques are used to simplify genetic programs. The simplification based GP system is examined and compared to a standard GP system on a regression problem and a classification problem. The results suggest that, at certain frequencies or proportions, this system can not only achieve superior performance to the standard system on these problems, but also significantly reduce the sizes of evolved programs.