论文标题
自然语言状态表示强化学习的概述
An Overview of Natural Language State Representation for Reinforcement Learning
论文作者
论文摘要
合适的国家代表性是增强学习过程中学习过程的基本组成部分。在各种任务中，国家可以用自然语言描述，也可以是自然语言本身。这项调查概述了文献中用于建立自然语言状态表示的策略。我们呼吁更语言解释和扎实的表示，仔细的设计决策理由以及对不同方法有效性的评估。
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.
