For the compositions comparing RL-CSP, Uniform and Original policies, Fig. shows that RL-CSP is fastest to locate the global minimum for three compositions (Y2TiO5, Y2Ti2O7 and SrY2O4), and the second fastest for two; Sr4Ti3O10 behind Uniform and Y2O3 behind Original. The latter case is discussed in detail in the subsequent section, the analysis of the former case reveals that although RL-CSP does not improve upon the Uniform policy for Sr4Ti3O10, the difference between their Nmean (144 steps) is relatively small. Thus, we conclude that the efficiency of RL-CSP is comparable to that of Uniform, and that the lack of improvement from learning in Sr4Ti3O10 can be attributed to the limited duration of the runs in this case.