Dragonfly: a modular deep reinforcement learning library

Amirhossein Bateni; Elie Hachem; Jonathan Viquerat; Paul Garnier

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Dragonfly: a modular deep reinforcement learning library

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arxiv 2505.03778 v2 pith:7QQNY3IN submitted 2025-04-30 cs.LG

Dragonfly: a modular deep reinforcement learning library

Jonathan Viquerat , Paul Garnier , Amirhossein Bateni , Elie Hachem This is my paper

classification cs.LG

keywords deepdragonflylearninglibraryreinforcementagentsallowsbenchmarks

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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.

Dragonfly: a modular deep reinforcement learning library

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