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An Overview of Natural Language State Representation for Reinforcement Learning

arXiv 2007.09774 ↗First posted 19 Jul 2020cs.CLcited by 6

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Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jul 2020.

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Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 1; 2025: 1.

6 papers.