Relation

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

The experiments evaluating deep reinforcement learning for personalizing review sessions on e-learning platforms consist of establishing the experimental setup, determining reward functions and performance metrics, and training the LSTM. The evaluation phase includes analyzing the relation between rewards and thresholds, testing the RL agent's performance when the number of items varies, comparing the TRPO and TNPG algorithms, comparing likelihood and average of sum of outcomes based reward functions, and assessing the performance of TRPO with reward shaping.

0

1

Updated 2026-07-04

Tags

Data Science

Learn After