ChemGymRL: A customizable interactive framework for reinforcement finding out for virtual chemistry

Digital Discovery, 2024, 3,742-758
DOI: 10.1039/D3DD00183K, Paper

Open Access

&nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague, Mark Baula, Nouha Chatti, Amanuel Dawit, Xinkai Li, Nicholas Paquin, Mitchell Shahen, Zihan Yang, Colin Bellinger, Mark Crowley, Isaac Tamblyn
Demonstration of a new open source Python library for simulating chemistry experiments as a gymnasium-API, reinforcement learning environment. Allowing learning policies for material design tasks or pipelines using a modular, extendable design.
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