Research map / Reinforcement learning / Imitation learning
Learning Safe Policies with Expert Guidance
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use maxmin planning instead of selecting a random reward for the unknown terrain | Gridworld policy · Gridworld with an unknown fifth terrain type | avoidance of unknown terrain | Helped |
| Use maxmin planning under stochastic transitions | Gridworld policy · Gridworld with stochastic transitions | unknown-terrain traversal | Helped |
| Add Expert B's demonstration to Expert A's demonstration | CartPole maxmin policy · CartPole with two question blocks | safe travel range | Mixed |
Closest papers by meaning
- Advice-Guided Reinforcement Learning in a non-Markovian Environment (AAAI 2021 · similarity 0.89)
- Safe Reinforcement Learning by Imagining the Near Future (NeurIPS 2021 · similarity 0.89)
- Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation (NeurIPS 2024 · similarity 0.88)
- A Provable Approach for End-to-End Safe Reinforcement Learning (NeurIPS 2025 · similarity 0.87)
- Probabilistic Shielding for Safe Reinforcement Learning (AAAI 2025 · similarity 0.87)
- Sampling-Based Safe Reinforcement Learning (NeurIPS 2026 · similarity 0.87)
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