{"type":"ScholarlyArticle","title":"Compositional Neural Logic Programming","authors":[{"name":"Son N. Tran","slug":"son-n-tran","given":"Son N.","family":"Tran","affiliation":""}],"abstract":"This paper introduces Compositional Neural Logic Programming (CNLP), a framework that integrates neural networks and logic programming for symbolic and sub-symbolic reasoning. We adopt the idea of compositional neural networks to represent first-order logic predicates and rules. A voting backward-forward chaining algorithm is proposed for inference with both symbolic and sub-symbolic variables in an argument-retrieval style. The framework is highly flexible in that it can be constructed incrementally with new knowledge, and it also supports batch reasoning in certain cases. In the experiments, we demonstrate the advantages of CNLP in discriminative tasks and generative tasks.","doi":"10.24963/ijcai.2021/421","url":"https://ijcai.org/proceedings/2021/421","pdf":"https://ijcai.org/proceedings/2021/0421.pdf","markdown":"https://ijcai.org/proceedings/2021/421.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/421","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Machine Learning","track":"Main Track","number":421,"pages":{"first":3059,"last":3066},"keywords":["Machine Learning: Neuro-Symbolic Methods","Knowledge Representation and Reasoning: Leveraging Knowledge and Learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}