An Overview of Natural Language State Representation for Reinforcement LearningDownload PDF

12 Jun 2020 (modified: 17 Jul 2020)ICML 2020 Workshop LaReL Blind SubmissionReaders: Everyone
  • Abstract: A suitable state representation is a fundamental part of the learning process in Reinforcement Learning. In various tasks, the state can either be described by natural language or be natural language itself. This survey outlines the strategies used in the literature to build natural language state representations. We appeal for more linguistically interpretable and grounded representations, careful justification of design decisions and evaluation of the effectiveness of different approaches.
  • TL;DR: A survey of approaches to model natural language state representations in NLP tasks that adopt reinforcement learning methods.
  • Keywords: reinforcement learning, natural language, state representation
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