What is it about?
We use reinforcement learning as a hands-off approach to determine the pathway with the lowest energy barrier between two states. We investigate different existing reinforcement learning algorithms for this task and come up with a hybrid of the state-of-the-art algorithms which performs best at this task.
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Why is it important?
Traditional methods to find reaction pathways usually use variations of gradient descent and might get stuck in a local minima. Using a self-learning reinforcement learning technique allows exploration of the potential energy surface and a higher chance of locating the optimal pathway with a lower energy barrier.
Perspectives
This work allowed me to apply ideas learnt in the classroom to an out-of-the-box field and learn about the challenges that come along with working on such cross-disciplinary problems.
Adittya Pal
Syddansk Universitet
Read the Original
This page is a summary of: Estimating reaction barriers with deep reinforcement learning1, Data Science, October 2024, SAGE Publications,
DOI: 10.3233/ds-240063.
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