The exploration process for the optimal reliability levels using DyRAMO is shown in Fig. . For comparison, the results of randomly adjusting the reliability levels are also presented. Fig. shows the evolution of the DSS score during BO-based and random exploration. In BO-based exploration, the DSS score increased as exploration progressed, eventually reaching approximately 0.38. In contrast, during random exploration, the DSS score fluctuated between 0.0 and 0.2 throughout. This demonstrates that the BO efficiently identified a combination of appropriate reliability levels that yielded a high DSS score. Figs. and represent the evolution of the explored reliability levels and the scaled predicted properties of the designed molecules, respectively. Each scaled predicted property in each exploration step is calculated by extracting the designed molecules with the top 10% average of the three scaled properties from all designed molecules, and then averaging each scaled property for these extracted molecules. The explored reliability levels stabilized late in the exploration process and converged at approximately 0.60 for inhibitory activity against EGFR, and 0.40 for metabolic stability and membrane permeability, respectively. The predicted properties were optimized as exploration progressed. Fig. illustrates how DyRAMO balances the desirability of the reliability levels and predicted properties. At the beginning of the exploration, either the average reliabilities or scaled properties are high, or both are low. However, as the exploration progresses, it can be seen that the exploration moves toward the upper right in an attempt to optimize both the averaged reliabilities and scaled properties. Fig. shows that it is difficult to conduct efficient random exploration. These results demonstrated the efficiency of BO-based exploration in DyRAMO for designing molecules while avoiding reward hacking.