[강연] Toward a Tractable Solution for Human-in-the-loop Reinforcement Learning: Algorithm and Benchmark (Kimin Lee, 서울대 AI여름학교 2021)

https://www.youtube.com/watch?v=lL-nq8zhi18 

• Reward engineering 문제와 reward exploitation문제를 해결하고자 human perference가 반영된 reward를 sequential query로부터 학습
• Human-in-the-loop RL

 

• 관련 papers:

1. PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training (ICML 2021)
   - Paper link: https://arxiv.org/abs/2106.05091
   - Site: https://sites.google.com/view/icml21pebble
   - Code: https://github.com/pokaxpoka/B_Pref
2. B-Pref: Benchmark for Preference-based RL (NeurIPS 2021, Track)
   - Openreview link: https://openreview.net/forum?id=ps95-mkHF_ d
   - Code: https://github.com/pokaxpoka/B_Pref