• Corpus ID: 244488408

Learning Symbolic Rules for Reasoning in Quasi-Natural Language

@article{Yang2021LearningSR,
  title={Learning Symbolic Rules for Reasoning in Quasi-Natural Language},
  author={Kaiyu Yang and Jia Deng},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.12038}
}
Symbolic reasoning, rule-based symbol manipulation, is a hallmark of human intelligence. However, rule-based systems have had limited success competing with learning-based systems outside formalized domains such as automated theorem proving. We hypothesize that this is due to the manual construction of rules in past attempts. In this work, we ask how we can build a rule-based system that can reason with natural language input but without the manual construction of rules. We propose MetaQNL, a… 

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