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EUROGP
2008
Springer

Exposing a Bias Toward Short-Length Numbers in Grammatical Evolution

13 years 12 months ago
Exposing a Bias Toward Short-Length Numbers in Grammatical Evolution
Many automatically-synthesized programs have, like their hand-made counterparts, numerical parameters that need to be set properly before they can show an acceptable performance. Hence, any approach to the automatic synthesis of programs needs the ability to tune numerical parameters efficiently. Grammatical Evolution (GE) is a promising grammar-based genetic programming technique that synthesizes numbers by concatenating digits. In this paper, we show that a naive application of this approach can lead to a serious number length bias that in turn affects efficiency. The root of the problem is the way the context-free grammar used by GE is defined. A simple, yet effective, solution to this problem is proposed.
Marco Antonio Montes de Oca
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where EUROGP
Authors Marco Antonio Montes de Oca
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