DRL-SRS: A Deep Reinforcement Learning Approach for Optimizing Spaced Repetition Scheduling
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DOI: 10.3390/app14135591
Abstract: Optimizing spaced repetition schedules is of great importance for enhancing long-term memory retention in both real-world applications, e.g., online learning platforms, and academic applications, e.g., cognitive science. Traditional methods tackle this problem by employing handcrafted… read more here.
Keywords: repetition scheduling; optimizing spaced; repetition; spaced repetition ... See more keywords