Figure investigates the Tanimoto similarity to the corresponding input compound changes as RL steps progress. It can be seen that RL noDF mostly maintains a decent similarity as RL steps increase, while RL DF(cmp) exhibits a declining similarity but mostly above 0.5. RL DF(cmp) encourages the generation of more unique compounds with improved properties than RL noDF (as shown in Figure ) at the expense of reduced similarity. RL DF(cmp) Sim helps to increase similarity compared to RL DF(cmp) (Figure ) and leads to more unique compounds with similarity above 0.7 and improved properties than RL noDF and RL DF(cmp) as shown in Figure .