Deep reinforcement learning of transition states
Jun Zhang, Yao-Kun Lei, Zhen Zhang, Xu Han, Maodong Li, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao
Abstract
RL<sup>‡</sup>can automatically locate the transition states of chemical reactions through deep reinforcement learning of feedback from molecular simulations.
Topics & Concepts
Reinforcement learningComputer scienceFunction (biology)State (computer science)Value (mathematics)Artificial intelligenceArtificial neural networkPath (computing)Bellman equationQ-learningTransition (genetics)Mechanism (biology)Chemical reactionStatistical physicsSampling (signal processing)Dynamics (music)Dynamic programmingReinforcementTerm (time)Reaction dynamicsMathematicsTransition stateMolecular dynamicsCurrent (fluid)AlgorithmMachine Learning in Materials ScienceQuantum many-body systemsNeural Networks and Reservoir Computing