In an ideal case, the graph should indicate the highest values in the beginning and the lowest values at the end, thus indicating that the algorithm picks the condition which will deliver a high yield during the first iterations. Of course, this is unrealistic as the model requires a certain number of iterations to screen the chemical space and understand in which region the maximum is located. The plot for exploitation (Figure ) demonstrates that the initial search started in a region of the chemical space which delivered high yields and the model seem to exploit this area. However, since no exploration was used for sampling, the global maximum (slightly higher than the datapoints which were sampled in the beginning) could only be found after more than 100 iterations. The two peaks indicate that the model only found these two high yielding regions after the area around the initial data was exploited. By contrast, Figure illustrates that EI samples a priori over a broader space (many high and low values are sampled and the curve is noisier) due to the explorative character and then more steadily reaches low yielding areas of the chemical space. In a direct comparison, this method often allows for finding the optimal conditions in fewer experiments than just exploitative search.