At each round, the user model is initialized with 10 randomly chosen molecules, and the priors of the user-model are defined by the previous round's 𝜽 𝑟-1 (𝜽 0 in the first round). Then, we do 10 iterations of querying 𝑛 𝑏𝑎𝑡𝑐ℎ = 10 molecules in batches. This means that we query in total 𝑇 = 110 molecules from a simulated chemist, making the total query budget in the experiment 220. The simulated chemist gives feedback 1 randomly with probability of 𝑆 𝑚𝑄𝐸𝐷 (𝑥). For each query strategy described in Section 2.2.3, we repeat the experiment ten times with different random seeds to quantify variance due to different 𝐷 0 and stochasticity in the simulated chemist's answers.