These are the parameters used by the authors for their experiments:

1. $n = 30$ (number of items)
2. $T = 200$ (number of steps)
3. $D = 5$ (delay between steps in seconds)
4. For the EFC (Exponential Forgetting Curve) student model, the sample item difficulty ($\theta$) is from the distribution: $\log\theta \sim \mathcal{N}(\log(0.077), 1)$
5. For the HLR (Half-Life Regression) student model: $\overrightarrow{\theta} = (1, 1, 0, \theta_3)$ where $\theta_3 \sim \mathcal{N}(0, 1)$; and $\overrightarrow{x_i} =$ (number of attempts, number correct, number incorrect, one-hot encoding of item $i$ out of $n$ items).
6. For the GPL (Generalized Power-Law) student model: $a = \overrightarrow{\alpha} = 0$; $d \sim \mathcal{N}(1, 1)$; $\log \overrightarrow{d} \sim \mathcal{N}(0, 1)$; $\log r \sim \mathcal{N}(0, 0.01)$; $W = 5$; $\theta_{2w} = \theta_{2w - 1} = \frac{1}{\sqrt{W} - w + 1}$
7. For the TRPO algorithm, the batch size is 4000, $\gamma = 0.99$, and the step size is 0.01.
8. For the Recurrent Network Policy, the number of hidden layers is 32.