Research map / Reinforcement learning / Imitation learning
Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add expert-demonstration MC error term to OGAPI regret (ablation on N1 not run; theory only) | OGAPI · online GAIL theory | regret | No clear effect |
| pessimism via uncertainty quantifiers on additional dataset (no sufficient-coverage assumption) | PGAPI · offline GAIL theory | optimality gap | No clear effect |
| assume sufficient coverage on additional dataset | PGAPI · offline GAIL theory | optimality gap | Helped |
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