Conference Proceeding

Error thresholds and their relation to optimal mutation rates



Ochoa G, Harvey I & Buxton H (1999) Error thresholds and their relation to optimal mutation rates. In: Floreano D, Nicoud J & Mondada F (eds.) Advances in Artificial Life: 5th European Conference, ECAL’99 Lausanne, Switzerland, September 13–17, 1999 Proceedings. Lecture Notes in Computer Science, 1674. 5th European Conference on Advances in Artificial Life, ECAL’99, Lausanne, Switzerland, 13.09.1999-17.09.1999. Berlin Heidelberg: Springer, pp. 54-63.;

The error threshold - a notion from molecular evolution - is the critical mutation rate beyond which structures obtained by the evolutionary process are destroyed more frequently than selection can reproduce them. We argue that this notion is closely related to the more familiar notion of optimal mutation rates in Evolutionary Algorithms (EAs). This correspondence has been intuitively perceived before ([9], [11]). However, no previous study, to our knowledge, has been aimed at explicitly testing the hypothesis of such a relationship. Here we propose a methodology for doing so. Results on a restricted range of fitness landscapes suggest that these two notions are indeed correlated. There is not, however, a critically precise optimal mutation rate but rather a range of values producing similar near-optimal performance. When recombination is used, both error thresholds and optimal mutation ranges are lower than in the asexual case. This knowledge may have both theoretical relevance in understanding EA behavior, and practical implications for setting optimal values of evolutionary parameters.

Title of seriesLecture Notes in Computer Science
Number in series1674
Publication date31/12/1999
Publication date online30/09/1999
Publisher URL
Place of publicationBerlin Heidelberg
ISSN of series0302-9743
Conference5th European Conference on Advances in Artificial Life, ECAL’99
Conference locationLausanne, Switzerland

People (1)


Professor Gabriela Ochoa

Professor Gabriela Ochoa

Professor, Computing Science