Concept

Experiments (Using deep reinforcement learning for personalizing review sessions on e-learning platforms with spaced repetition)

  1. Experimental Setup
  2. Reward functions and performance metrics
  3. Training the LSTM
  4. Relation between rewards and thresholds
  5. Performance of RL agent when the number of items are varied
  6. Performance of TRPO vs. TNPG algorithms
  7. Comparison between likelihood and average of sum of outcomes based reward functions (research objective)
  8. Performance of TRPO with reward shaping (research objective)
  9. Evaluation

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Updated 2020-10-29

Tags

Data Science

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