Learning Free Energy Pathways through Reinforcement Learning of Adaptive Steered Molecular Dynamics
N. Ho, J. K. Cava, J. Vant, A. Shukla, J. Miratsky, P. Turaga, R. Maciejewski, A. Singharoy
This paper develops a reinforcement learning framework to compute low free energy pathways between states using adaptive steered molecular dynamics and robotics planning.
bioRxiv · Oct 4, 2022 · PreprintBiophysics