Equation 1 states that the probability of generating a given SMILES, x, is equal to the product of the probabilities of generating a token at time-step t, given the sequence so far at time-step t -1. The model is pre-trained on a dataset of molecules (ChEMBL 61 for the main experiments and ZINC for the benchmarking experiment) to yield the Prior which is parameterized by the weights θ. The Agent is initialized identical to the Prior but is fine-tuned during the reinforcement learning (RL) process. The Augmented Likelihood is defined as a linear combination between the Prior and a reward term (Equation ):