Only the combination of mathematics and agent-based simulations can leverage the full potential of evolutionary modeling

Hilbe, Christian; Traulsen, Arne

doi:10.1016/j.plrev.2016.10.004

Cited by 3 publications

(2 citation statements)

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“…In a comment on 106 , Tarnita 107 argues that new mathematical methods should still be searched for to solve previously mathematically intractable cases. Another comment on this gives an example of a whole set of strategies that can be explored with mathematics, but that would have been invisible to agent-based simulations alone 108 . Thus, mathematics and simulations complement each other.…”

Section: Discussionmentioning

confidence: 99%

Computation and Simulation of Evolutionary Game Dynamics in Finite Populations

Hindersin

Traulsen

et al. 2019

Sci Rep

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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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Section: Discussionmentioning

confidence: 99%

Computation and Simulation of Evolutionary Game Dynamics in Finite Populations

Hindersin

Traulsen

et al. 2019

Sci Rep

Self Cite

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“…2 A recent paper by Adami et al (2016a) has triggered a lively discussion about the role of agent-based simulations in evolutionary game theory-see the responses by Bellomo and Elaiw (2016), Hilbe and Traulsen (2016), Schuster (2016) and Tarnita (2016). These responses and the authors' reply (Adami et al (2016b)) reveal a growing understanding of the complementary roles of simulation and analysis.…”

Section: Exact Analysis Approximation and Simulation Of Population Dynamicsmentioning

confidence: 99%

An introduction to ABED: Agent-based simulation of evolutionary game dynamics

Izquierdo

Sandholm

2019

Games and Economic Behavior

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ABED is free and open-source software for simulating evolutionary game dynamics in finite populations. We explain how ABED can be used to simulate a wide range of dynamics considered in the literature and many novel dynamics. In doing so, we introduce a general model of revisions for dynamic evolutionary models, one that decomposes strategy updates into selection of candidate strategies, payoff determination, and choice among candidates. Using examples, we explore ways in which simulations can complement theory in increasing our understanding of strategic interactions in finite populations.

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