{"type":"ScholarlyArticle","title":"Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective","authors":[{"name":"Luís C. Lamb","slug":"luis-c-lamb","given":"Luís C.","family":"Lamb","affiliation":""},{"name":"Artur d’Avila Garcez","slug":"artur-d-avila-garcez","given":"Artur d'Avila","family":"Garcez","affiliation":""},{"name":"Marco Gori","slug":"marco-gori","given":"Marco","family":"Gori","affiliation":""},{"name":"Marcelo O.R. Prates","slug":"marcelo-o-r-prates","given":"Marcelo O.R.","family":"Prates","affiliation":""},{"name":"Pedro H.C. Avelar","slug":"pedro-h-c-avelar","given":"Pedro H.C.","family":"Avelar","affiliation":""},{"name":"Moshe Y. Vardi","slug":"moshe-y-vardi","given":"Moshe Y.","family":"Vardi","affiliation":""}],"abstract":"Neural-symbolic computing has now become the subject of interest of both academic and industry research laboratories. \r\nGraph Neural Networks (GNNs) have been widely used in relational and symbolic domains, with widespread application of GNNs in combinatorial optimization, constraint satisfaction, relational reasoning and other scientific domains.\r\nThe need for improved explainability, interpretability and trust of AI systems in general demands principled methodologies, as suggested by neural-symbolic computing. \r\nIn this paper, we review the state-of-the-art on the use of GNNs as a model of neural-symbolic computing. This includes the application of GNNs in several  domains as well as their relationship to current developments in neural-symbolic computing.","doi":"10.24963/ijcai.2020/679","url":"https://ijcai.org/proceedings/2020/679","pdf":"https://ijcai.org/proceedings/2020/0679.pdf","markdown":"https://ijcai.org/proceedings/2020/679.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/679","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Survey track","track":"Survey track","number":679,"pages":{"first":4877,"last":4884},"keywords":["Constraints and Satisfiability: general","Safe, Explainable, and Trustworthy AI: general","Machine Learning: general","Knowledge Representation and Reasoning: general"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}