2 papers
cs.RO2026
Discriminative Barrier Functions for Safe Adversarial Imitation Learning from Observation
Anubhav Vishwakarma, Bhaumik Mehta, Caleb Hsu +3
Inverse Reinforcement Learning (IRL) algorithms are powerful tools for learning from and generalizing expert demonstrations, but they often rely on unconstrained exploration, rende…
cs.RO2025
Model Predictive Adversarial Imitation Learning for Planning from Observation
Tyler Han, Yanda Bao, Bhaumik Mehta +8
Human demonstration data is often ambiguous and incomplete, motivating imitation learning approaches that also exhibit reliable planning behavior. A common paradigm to perform plan…