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Journal Article

Computation and simulation of evolutionary game dynamics in finite populations

MPS-Authors
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Hindersin,  Laura
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Traulsen,  Arne
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

Fulltext (public)

Hindersin_SciRep_2019.pdf
(Publisher version), 3MB

Supplementary Material (public)

41598_2019_43102_MOESM1_ESM.pdf
(Supplementary material), 2MB

Citation

Hindersin, L., Wu, B., Traulsen, A., & Garcia, J. (2019). Computation and simulation of evolutionary game dynamics in finite populations. Scientific Reports, 9: 6946. doi:10.1038/s41598-019-43102-z.


Cite as: http://hdl.handle.net/21.11116/0000-0003-A46A-D
Abstract
The study of evolutionary dynamics increasingly relies on computational methods, as more and more cases outside the range of analytical tractability are explored. The computational methods for simulation and numerical approximation of the relevant quantities are diverging without being compared for accuracy and performance. We thoroughly investigate these algorithms in order to propose a reliable standard. For expositional clarity we focus on symmetric 2 × 2 games leading to one-dimensional processes, noting that extensions can be straightforward and lessons will often carry over to more complex cases. We provide time-complexity analysis and systematically compare three families of methods to compute fixation probabilities, fixation times and long-term stationary distributions for the popular Moran process. We provide efficient implementations that substantially improve wall times over naive or immediate implementations. Implications are also discussed for the Wright-Fisher process, as well as structured populations and multiple types.