Comparing the impact of these parameters on the number of hit scaffolds generated (Figure /E/G), we observe that simply increasing 𝑁 batch has a dramatic impact on oracle call efficiency, resulting in up to 537±67 scaffolds for the largest batch size of 2048, a 3.83 fold increase over the RL-AL baseline case and 15.34 fold improvement over pure RL (Figure ). Importantly, runs with larger 𝑁 batch also become productive much earlier, requiring only approximately 5000 oracle calls to become productive. The diversity of generated hit scaffolds at the largest batch size (2048) is slightly reduced to 0.252±0.032 compared with 0.199±0.016 and 0.178±0.028 for RL-AL-and RL-baseline respectively (Figure ), but the significantly larger number of generated hits likely offsets this in practice. Reducing 𝑁 acquired has the same effect as increasing 𝑁 batch , resulting in faster lift-off and up to 582±253 scaffolds identified for the smallest 𝑁 acquired of 32 (Figure ). The resulting hit scaffold diversity for this case is 0.255±0.022 (Figure ). The similar behavior of these extreme cases can be rationalized by their similar, low AL/RL ratios -0.0625 and 0.125 respectively.