With HLR student model (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
No major variations have been noticed in the performance of the DLR agent with HLR relative to the random policy for both likelihood and log likelihood reward functions as the number of items was increased.
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With HLR student model (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
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Impact of Varying Item Counts on DRL Agent Performance with DASH (GPL) Student Model (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)