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The response of populations of digital organisms that adapt to a time-varying fitness landscape of two oscillating peaks is studied, corroborating in general predictions from quasi-species theory in dynamic landscapes such as adaptation to the average fitness landscape at small periods and quasistatic adaptation at large periods.

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The response of populations of digital organisms that adapt to a time-varying fitness landscape of two oscillating peaks is studied, corroborating in general predictions from quasi-species theory in dynamic landscapes such as adaptation to the average fitness landscape at small periods and quasistatic adaptation at large periods.

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The tunably rugged NK-model is used to study avalanche-like events that occur when environmental change causes fitness optima to disappear, and average values of Delta increase logarithmically with system size.

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A new model for horizontal gene transfer is provided and it is shown how it drives evolutionary dynamics in populations exhibiting a high or a low competence for HGT, demonstrating how frequently occuring HGT can lead to an evolutionary state where no distinct species can be distinguished.

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Based on the Eigen and Crow?Kimura models with a single-peak fitness landscape, we propose the fitness values of all sequence types to be Gaussian distributed random variables to incorporate the…

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