Language and (Meta-) RL: An ode to structure

Aditya Mohan

Keywords: NLP, Reinforcement Learning, Meta-Learning, Meta-RL

Abstract: It has been argued that language can be a very powerful way to compress information about the world. In fact, the learning of humans is significantly sped up around the time they start understanding and using language. A natural question, then, is whether the same can be argued for sequential decision-making systems that either learn to optimize a single or multiple, task. To this end, there has been a surge of works exploring the use of Language in Reinforcement Learning (RL) and Meta-RL. The goal of this blog post is to try and explain some of the recent works in this sub-field and help elucidate how language can help with incorporating structure about the environment to improve learning generalization in (Meta) RL

Blogpost Url: https://iclr-blogposts.github.io/staging/blog/2023/language-rl/

ICLR Papers: https://arxiv.org/abs/2112.03753

ID Of The Authors Of The ICLR Paper: ~Andrew_Kyle_Lampinen1

Conflict Of Interest: No