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Computation and Simulation of Evolutionary Game Dynamics in Finite Populations

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...

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Autores principales: Hindersin, Laura, Wu, Bin, Traulsen, Arne, García, Julian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6502801/
https://www.ncbi.nlm.nih.gov/pubmed/31061385
http://dx.doi.org/10.1038/s41598-019-43102-z
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author Hindersin, Laura
Wu, Bin
Traulsen, Arne
García, Julian
author_facet Hindersin, Laura
Wu, Bin
Traulsen, Arne
García, Julian
author_sort Hindersin, Laura
collection PubMed
description 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.
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spelling pubmed-65028012019-05-20 Computation and Simulation of Evolutionary Game Dynamics in Finite Populations Hindersin, Laura Wu, Bin Traulsen, Arne García, Julian Sci Rep Article 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. Nature Publishing Group UK 2019-05-06 /pmc/articles/PMC6502801/ /pubmed/31061385 http://dx.doi.org/10.1038/s41598-019-43102-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Hindersin, Laura
Wu, Bin
Traulsen, Arne
García, Julian
Computation and Simulation of Evolutionary Game Dynamics in Finite Populations
title Computation and Simulation of Evolutionary Game Dynamics in Finite Populations
title_full Computation and Simulation of Evolutionary Game Dynamics in Finite Populations
title_fullStr Computation and Simulation of Evolutionary Game Dynamics in Finite Populations
title_full_unstemmed Computation and Simulation of Evolutionary Game Dynamics in Finite Populations
title_short Computation and Simulation of Evolutionary Game Dynamics in Finite Populations
title_sort computation and simulation of evolutionary game dynamics in finite populations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6502801/
https://www.ncbi.nlm.nih.gov/pubmed/31061385
http://dx.doi.org/10.1038/s41598-019-43102-z
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