Training the LSTM (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
The LSTM was used in order to predict the DRL rewards. The 10000 interaction data was divided into 8000 2000 for the train and validation sets respectively.
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Experimental Setup (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Reward functions and performance metrics (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Training the LSTM (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Relation between rewards and thresholds (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Performance of RL agent when the number of items are varied (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Performance of TRPO vs. TNPG algorithms (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Performance of TRPO with reward shaping (research objective) (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Comparison between likelihood and average of sum of outcomes based reward functions (research objective) (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)
Evaluation (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)