Preprint
Jul 2026
Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation
This work constraining reward function candidacy during IRL to the space of CBFs yields a formulation that exhibits safe online control with continuous experiential improvement, and demonstrates that the recovered barrier function is robust to unsafe states entirely absent from the expert data.
Anubhav Vishwakarma, Bhaumik Mehta, Caleb Hsu et al.
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