Artificial Intelligence

    

Improving Multi Expression Programming: an Ascending Trail from Sea-level Even-3-parity Problem to Alpine Even-18-Parity Problem

Authors: Mihai Oltean

Multi Expression Programming is a Genetic Programming variant that uses a linear representation of individuals. A unique feature of Multi Expression Programming is its ability of storing multiple solutions of a problem in a single chromosome. In this paper, we propose and use several techniques for improving the search performed by Multi Expression Programming. Some of the most important improvements are Automatically Defined Functions and Sub-Symbolic node representation. Several experiments with Multi Expression Programming are performed in this paper. Numerical results show that Multi Expression Programming performs very well for the considered test problems.

Comments: 36 Pages. chapter 10, Evolvable Machines: Theory and Applications, Springer-Verlag, edited by Nadia Nedjah (et al.), pp. 229-255, 2004

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[v1] 2022-02-14 01:51:37

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