Offline RL

Human-Centric Dialog Training via Offline Reinforcement Learning
We train dialog models with interactive data from conversations with real humans, using a novel Offline RL technique based on KL-control. Rather than rely on manual ratings, we learn from implicit signals like sentiment, and show that this results in better performance.
Natasha Jaques*, J. H. Shen*, A. Ghandeharioun, C. Ferguson, A. Lapedriza, N. Jones, S. Gu, R. Picard
2020 In Empirical Methods in Natural Language Processing (EMNLP)
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Human-Centric Dialog Training via Offline Reinforcement Learning