In this episode, we invite Hal Daumé to continue the discussion on reinforcement learning, focusing on how it has been used in NLP. We discuss how to reduce NLP problems into the reinforcement learning framework, and circumstances where it may or may not be useful. We discuss imitation learning, roll-in and roll-out, and how to approximate an expert with a reference policy. 

DAgger: https://www.semanticscholar.org/paper/A-Reduction-of-Imitation-Learning-and-Structured-to-Ross-Gordon/17eddf33b513ae1134abadab728bdbf6abab2a05?navId=citing-papers
RESLOPE: http://legacydirs.umiacs.umd.edu/~hal/docs/daume18reslope.pdf

75 - Reinforcement / Imitation Learning in NLP, with Hal Daumé III

**The podcast is currently on hiatus. For more active NLP content, check out the Holistic Intelligence Podcast linked below.**

Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.

75 - Reinforcement / Imitation Learning in NLP, with Hal Daumé III

NLP Highlights