Signal-to-noise, Crosstalk, and Long Range Problem Difficulty in Genetic Algorithms

This paper presents a signal-to-noise perspective of the search bias introduced by genetic algorithms. A decision theoretic signal-to-noise framework is used to show that there are two fundamental modes of introducing diiculty through search bias: 1) sending a wrong signal and 2) increasing or decreasing noise depending on the direction of signal. The main purpose of this paper is to identify crosstalk as another possible source of problems , caused by search bias in genetic algorithms. I show that a small modiication of the one-max problem can convert it to dii-cult to solve because of crosstalk. This paper also studies the royal road functions (Forrest and Mitchell, 1994) and demonstrates that crosstalk plays a major role in making R2 harder than R1 to solve. This clearly shows that increasing signal in the right direction alone does not necessarily make a problem easy for GA, unless the noise is also reduced.

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