Playing by the Book: Towards Agent-based Narrative Understanding through Role-playing and Simulation.

arXiv: Learning(2018)

引用 23|浏览40
暂无评分
摘要
Understanding procedural text requires tracking entities, actions and effects as the narrative unfolds (often implicitly). We focus on the challenging real-world problem of structured narrative extraction in the materials science domain, where language is highly specialized and suitable annotated data is not publicly available. We propose an approach, Text2Quest, where procedural text is interpreted as instructions for an interactive game. A reinforcement-learning agent completes the game by understanding and executing the procedure correctly, in a text-based simulated lab environment. The framework is intended to be more broadly applicable to other domain-specific and data-scarce settings. We conclude with a discussion of challenges and interesting potential extensions enabled by the agent-based perspective.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要