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Artif Life. 2004 Spring;10(2):123-34.

Digital evolution in time-dependent fitness landscapes.

Author information

1
California Institute of Technology, Pasadena, CA 91125, USA. yel@its.caltech.edu

Abstract

We study the response of populations of digital organisms that adapt to a time-varying (periodic) fitness landscape of two oscillating peaks. We corroborate in general predictions from quasi-species theory in dynamic landscapes, such as adaptation to the average fitness landscape at small periods (high frequency) and quasistatic adaptation at large periods (low frequency). We also observe adaptive phase shifts (time lags between a change in the fitness landscape and an adaptive change in the population) that indicate a low-pass filter effect, in agreement with existing theory. Finally, we witness long-term adaptation to fluctuating environments not anticipated in previous theoretical work.

PMID:
15107225
DOI:
10.1162/106454604773563559
[Indexed for MEDLINE]
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