Research map / Reinforcement learning / Imitation learning
Scalable Bayesian Inverse Reinforcement Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use AVRIL instead of EDM | MIMIC-III Ventilator action matching · MIMIC-III Ventilator | ACC: 0.882 \pm 0.011 -> 0.891 \pm 0.002 | Helped |
| Use AVRIL instead of EDM | MIMIC-III Ventilator action matching · MIMIC-III Ventilator | AUC: 0.920 \pm 0.002 -> 0.917 \pm 0.001 | Hurt |
| Use AVRIL instead of A-RL trained on AVRIL's learned reward | MIMIC-III Ventilator action matching · MIMIC-III Ventilator | APS: 0.927 \pm 0.002 -> 0.940 \pm 0.001 | Helped |
| Use AVRIL instead of A-RL trained on AVRIL's learned reward | MIMIC-III Ventilator + Antibiotics action matching · MIMIC-III Ventilator + Antibiotics | ACC: 0.718 \pm 0.010 -> 0.754 \pm 0.001 | Helped |
| Use AVRIL instead of EDM | MIMIC-III Ventilator + Antibiotics action matching · MIMIC-III Ventilator + Antibiotics | AUC: 0.873 \pm 0.002 -> 0.884 \pm 0.000 | Helped |
| Use AVRIL instead of EDM | MIMIC-III Ventilator + Antibiotics action matching · MIMIC-III Ventilator + Antibiotics | APS: 0.682 \pm 0.004 -> 0.708 \pm 0.002 | Helped |
Closest papers by meaning
- Approximated Variational Bayesian Inverse Reinforcement Learning for Large Language Model Alignment (AAAI 2025 · similarity 0.88)
- How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach (NeurIPS 2024 · similarity 0.88)
- Hybrid Inverse Reinforcement Learning (ICML 2024 · similarity 0.88)
- Recent Advancements in Inverse Reinforcement Learning (AAAI 2024 · similarity 0.88)
- Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces (NeurIPS 2024 · similarity 0.87)
- Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective (ICML 2024 · similarity 0.87)
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