论文标题
通过自然语言教义学习规范
Learning Norms via Natural Language Teachings
论文作者
论文摘要
要与人类互动，人工智能（AI）系统必须了解我们的社会世界。在这个世界上，规范在激励和指导代理方面起着重要作用。但是，很少有人提出了学习社会规范的计算理论。关于正常（IS）与规范性（应该）的区别之间的辩论也有很长的历史。许多人认为，能够学习概念并认识到差异对于所有社会代理人都是必要的。本文介绍并展示了一种从自然语言文本学习规范的计算方法，该方法既说明正常和规范的内容。它为日常人们培训AI系统的社会规范为基础。
To interact with humans, artificial intelligence (AI) systems must understand our social world. Within this world norms play an important role in motivating and guiding agents. However, very few computational theories for learning social norms have been proposed. There also exists a long history of debate on the distinction between what is normal (is) and what is normative (ought). Many have argued that being capable of learning both concepts and recognizing the difference is necessary for all social agents. This paper introduces and demonstrates a computational approach to learning norms from natural language text that accounts for both what is normal and what is normative. It provides a foundation for everyday people to train AI systems about social norms.
