Initial public release of the adaptive evolutionary game (AEG) pipeline for adaptive evolutionary games, including modular Python code and a demonstration notebook. AEG extend classical evolutionary game theory by allowing players’ strategies to evolve through trait coevolution mediated by eco-evolutionary feedbacks. The AEG pipeline is an open-source Python package for simulating trait-mediated and density-dependent interactions in multispecies systems. It models the coupled dynamics of population densities and continuous traits using a unified system of ordinary differential equations. Unlike traditional evolutionary games with fixed traits and static payoff matrices, AEG enables adaptive trait evolution that dynamically reshapes interaction payoffs over time. This allows researchers to investigate feedback-driven coevolutionary dynamics in complex adaptive ecological systems. Modular package structure: aeg/model.py – core mathematical definitions for population and trait dynamics aeg/simulation.py – simulation engine providing functions like run_simulation aeg/__init__.py – exposes key functions for easy import aeg.ipynb – demonstration notebook showing example simulations and visualization workflow Users can reproduce simulations directly from the notebook or import the AEG package in Python for custom experiments. The framework supports an arbitrary number of interacting players and flexible payoff matrix structures, enabling studies of multiple interaction types (e.g., cyclic dominance, competition, mutualistic, and predator-prey systems). Vectorized operations and modern numerical solvers ensure scalability, reproducibility, and transparency for evolutionary and theoretical ecology research.

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