The RL-CSP code was written in Python and requires MySQL server to store the learning process variables. The University of Liverpool parallel Linux cluster nodes (40 cores 384 Gb memory each) were used to run the code. FUSE with different policies and compositions was run 600 times (40 runs for each of 3 policies and 5 compositions) allowing minimum 90,000 steps of BH search and was stopped earlier if the global minimum was found. The typical run of the fastest composition (Sr4Ti3O10) took ~24 hours whereas for the slowest composition (Y2O3), where only 30% (12 / 40) of runs on average manage to find the global minimum in 90,000 steps, the remaining runs took ~45 days till they passed 90,000 limit. MC-EMMA with different policies and one composition was run 120 times (40 runs for each of 3 policies) and all 120 runs stopped when the global minimum was found. The run took ~10 days on average while the longest run with the Uniform policy took ~72 days.