Uncertainty-Driven Replay Memory for Reinforcement Learning

arXiv:2608.29860 · cs.LG · Submitted 2026-08-30 · Read on arXiv

cs.LG

Submitted: 2026-08-30

Updated: 2026-08-30

Terminology

• Reinforcement Learning — 23× in this paper · explained in 4 episodes
• Epistemic Uncertainty — 14× in this paper · explained in 10 episodes
• Loss Function — 6× in this paper · explained in 2 episodes
• Uncertainty-Driven Replay Memory — 6× in this paper
• Deep Reinforcement Learning — 5× in this paper · explained in 2 episodes
• alpha — 5× in this paper · explained in 1 episode
• Generalization — 3× in this paper · explained in 13 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 3× in this paper · explained in 25 episodes
• Aleatoric Uncertainty — 2× in this paper · explained in 5 episodes
• Core — 2× in this paper · explained in 2 episodes
• Ensemble Learning — 2× in this paper · explained in 2 episodes
• Initial Data — 2× in this paper · explained in 2 episodes
• Uncertainty Quantification — 2× in this paper · explained in 8 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Action Space — 1× in this paper · explained in 1 episode
• Active Learning — 1× in this paper · explained in 6 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Information Gain — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Wasserstein Distance — 1× in this paper · explained in 4 episodes

Sources

• MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments

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