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Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning

NeurIPS 2022 · Reinforcement learning › Visual and representation RL · approach: Latent-space world models · 1 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Postpone augmentation distillation until after RL training (UCB-ExDA vs. UCB-InDA)UCB-based scheduling on Procgen · Heist (test-bg)score: 6.23$\pm$ 1.29 -> \bf{7.86}$\pm$ 0.83Helped
Postpone augmentation distillation until after RL training (UCB-ExDA vs. UCB-InDA)UCB-based scheduling on Procgen · Chaser (test-bg)score: 1.08$\pm$ 0.08 -> \bf{3. 18}$\pm$ 0.79Helped
Use UCB to choose augmentation or no augmentation during RL, then distill all augmentations afterwardPPO on Procgen · Heist (test-bg)score: 5.18 $\pm$ 1.53 -> \bf{7.86}$\pm$ 0.83Helped
Use UCB to choose augmentation or no augmentation during RL, then distill all augmentations afterwardPPO on Procgen · Chaser (test-lv)score: 4.83$\pm$ 0.88 -> 6.43$\pm$ 1.28Helped
Apply random-color augmentation through ExDA rather than InDAPPO on Procgen · Heist easybg (test-bg)normalized score: 1.92 -> 2.11Helped
Apply random-crop augmentation through InDA rather than ExDAPPO on Procgen · Heist easybg (test-lv)normalized score: 1.09 -> 1.80Helped
Use InDA rather than ExDA with random cropPPO on Procgen · Heist easybg (train)normalized score: 0.91 -> 1.25Helped
Add the option of no augmentation to UCB-InDA (ablation)UCB-InDA on Heist · Heist easybg (train)scoreHelped
Preserve the original policy response during augmented-observation distillation (DA rather than DrAC-style self-distillation) (ablation)Augmentation distillation on Procgen · Procgen, six-game averagenormalized scoreHelped
Separate PPO and distillation into alternating phases rather than optimize both simultaneously (ablation)Augmentation-aware PPO · Procgentrain performanceHelped
Add random black-image augmentation during RL training (ablation)InDA on Procgen · Heistscore: 9.2 $\pm$ 0.46 -> 6.72$\pm$0.419Hurt
Add random black-image augmentation during RL training (ablation)DrAC on Procgen · Chaserscore: 5.63$\pm$ 1.12 -> 1.49$\pm$0.036Hurt

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