Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
This release corresponds to the code used for the manuscript: "Reinforcement learning discovers new mechanisms of reentry in excitable media" The repository contains code for cellular automaton simulations, reinforcement-learning environments and training scripts, policy evaluation, simulations in the geometries studied in the manuscript, and generation of figures and analysis associated with the computational results. This release provides a fixed snapshot of the code corresponding to the current manuscript submission. Subsequent development of the repository may differ from this archived version.
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