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arXiv · 2505.03778

Dragonfly: a modular deep reinforcement learning library

Jonathan Viquerat·Paul Garnier·Amirhossein Bateni·Elie Hachem
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Abstract

Dragonfly is a deep reinforcement learning library focused on modularity, in order to ease experimentation and developments. It relies on a json serialization that allows to swap building blocks and perform parameter sweep, while minimizing code maintenance. Some of its features are specifically designed for CPU-intensive environments, such as numerical simulations. Its performance on standard agents using common benchmarks compares favorably with the literature.

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Jonathan Viquerat, Paul Garnier, Amirhossein Bateni, Elie Hachem. 2025-04-30. Dragonfly: a modular deep reinforcement learning library. https://arxiv.org/abs/2505.03778

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