Can evolution paths be explained by chance alone?
Abstract
We propose a purely probabilistic model to explain the evolution path of a population maximum fitness. We show that after n births in the population there are about n upwards jumps. This is true for any mutation probability and any fitness distribution and therefore suggests a general law for the number of upwards jumps. Simulations of our model show that a typical evolution path has first a steep rise followed by long plateaux. Moreover, independent runs show parallel paths. This is consistent with what was observed by Lenski and Travisano (1994) in their bacteria experiments.
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