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Self-Supervised Policy Adaptation during Deployment

ICLR 2021 · Reinforcement learning › Visual and representation RL · approach: Skill learning and diffusion policies · 60 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add online test-time inverse-dynamics adaptation to SAC+IDM (ablation)SAC+IDM · DMControl randomized colorsepisodic return: 406\scriptstyle{\pm29} -> 468\scriptstyle{\pm47}Helped
Add online test-time inverse-dynamics adaptation to SAC+IDMSAC+IDM · DMControl video backgroundsepisodic return: 7 out of 8 tasksMixed
Add online test-time inverse-dynamics adaptation to SAC+IDM (ablation)SAC+IDM · Real robot push, clothsuccess rate: 64\% -> 88\%Helped
Add online test-time inverse-dynamics adaptation to SAC+IDM (ablation)SAC+IDM · Simulated robot push, all dynamics changessuccess rate: 48\% -> 76\%Helped
Use rotation prediction rather than inverse dynamics for PAD (ablation)A2C navigation policy · CRLMazeepisodic returnMixed
Replace inverse dynamics with CURL and retain test-time adaptation (ablation)SAC policy · DMControl randomized colorsepisodic return: 445\scriptstyle{\pm99} -> 495\scriptstyle{\pm70}; 691\scriptstyle{\pm12} -> 588\scriptstyle{\pm22}Mixed
Replace inverse dynamics with rotation prediction and retain test-time adaptation (ablation)SAC policy · DMControl randomized colorsepisodic return: 335\scriptstyle{\pm7} -> 330\scriptstyle{\pm30}; 283\scriptstyle{\pm68} -> 230\scriptstyle{\pm53}Mixed
Discard policy updates after each step instead of carrying adaptation forward online (ablation)SAC+IDM (PAD) · DMControl randomized colorsepisodic return: 468\scriptstyle{\pm47} -> 441\scriptstyle{\pm16}; 797\scriptstyle{\pm46} -> 727\scriptstyle{\pm21}Mixed
Keep the self-supervised prediction head fixed during deployment adaptation (ablation)SAC+IDM (PAD) · DMControl randomized colorsepisodic return: 452\scriptstyle{\pm38} vs 468\scriptstyle{\pm47}; 802\scriptstyle{\pm41} vs 797\scriptstyle{\pm46}No clear effect
Continue self-supervised adaptation in the unchanged training environment (ablation)SAC+IDM (PAD) · DMControl training environmentsepisodic return: 911\scriptstyle{\pm24} -> 895\scriptstyle{\pm28}; 928\scriptstyle{\pm45} -> 927\scriptstyle{\pm45}No clear effect
Use PAD with inverse dynamics rather than no test-time adaptation (ablation)SAC+IDM · DMControl randomized colors, Cartpole balanceepisodic return: 835\scriptstyle{\pm40} -> 848\scriptstyle{\pm29}Mixed

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