Several others use reinforcement learning (RL) to develop an agent to predict read and write decisions (Satija and Pineau, 2016;Gu et al., 2017;Alinejad et al., 2018).
due to computational challenges, they pre-train an NMT model on full sentences and then train an agent that sees the fixed NMT model as part of its environment.