As shown in Figure , at each iteration, the trained MLP (discussed below) was eventually updated as the policy model 'decision maker' for the next iteration. The optimisation was terminated after 20 iterations, and the policy model at the last iteration became the final 'decision maker' to predict expected costs of molecules, and select reactions based on Eq. 5 to build retrosynthesis pathways.