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Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality

NeurIPS 2021 · Reinforcement learning › Imitation learning · approach: Offline imitation from imperfect data · 19 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use CAIL instead of 2IWIL (closest baseline)CAIL · Reacherexpected return: -23.055 -> -7.816Helped
use CAIL instead of 2IWILCAIL · Antexpected return: 3473.852 -> 3825.644Helped
use CAIL instead of 2IWILCAIL · Simulated Panda armexpected return: -120.622 -> -62.946Helped
use CAIL instead of 2IWIL/AIRLCAIL · Real UR5e armexpected return: -52.445 -> -34.330Helped
use CAIL instead of 2IWIL on success rateCAIL · Real robot armsuccess rate (%): 83 -> 100Helped
use CAIL instead of 2IWIL on success rateCAIL · Simulated robot armsuccess rate (%): 100 -> 100No clear effect
train only on non-optimal demonstrationsCAIL · Antexpected returnHelped
reduce ranking label ratio from 100% to 1% (ablation)CAIL · Reacherexpected return: -7.8 -> -8.0No clear effect
increase ranking label ratio from 1% to 100% (ablation)T-REX · Reacherexpected return: -83.7 -> -27.2Helped
increase ranking label ratio from 1% to 100% (ablation)2IWIL · Reacherexpected return: -33.5 -> -25.2No clear effect

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