EGTtools: Evolutionary game dynamics in Python
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Updated: Aug 1, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
Elias Fernández Domingos1,2, Francisco C Santos3, Tom Lenaerts1,2,4
1Machine Learning Group, ULB, Campus la Plaine, Brussels 1050, Belgium.
Abstract:
Evolutionary Game Theory (EGT) provides an important framework to study collective behavior. It combines ideas from evolutionary biology and population dynamics with the game theoretical modeling of strategic interactions. Its importance is highlighted by the numerous high level publications that have enriched different fields, ranging from biology to social sciences, in many decades. Nevertheless, there has been no open source library that provided easy, and efficient, access to these methods and models. Here, we introduce EGTtools, an efficient hybrid C++/Python library which provides fast implementations of both analytical and numerical EGT methods. EGTtools is able to analytically evaluate a system based on the replicator dynamics. It is also able to evaluate any EGT problem resorting to finite populations and large-scale Markov processes. Finally, it resorts to C++ and MonteCarlo simulations to estimate many important indicators, such as stationary or strategy distributions. We illustrate all these methodologies with concrete examples and analysis.
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