ChemGymRL: A customizable interactive framework for reinforcement learning for digital chemistry

Abstract

This paper provides a simulated laboratory for making use of Reinforcement Learning (RL) for material design, synthesis and discovery. Since RL is fairly data intensive, training agents `on-the-fly' by taking...