When Does Predictive Inverse Dynamics Outperform Behavior Cloning?

arXiv:2601.21718v2 Announce Type: replace Abstract: Behavior cloning (BC) is a practical offline imitation learning method, but it often fails when expert demonstrations are limited. Recent works have introduced a class of architectures named predictive inverse dynamics models (PIDM) that combine a future state predictor with an inverse dynamics model. While PIDM often outperforms BC, the reasons behind its benefits remain unclear. In this paper, we provide a theoretical explanation: PIDM introduces a bias-variance tradeoff. While predicting the future state introduces bias, conditioning the I

Source: arXiv cs.LG — read the full report at the original publisher.

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