{"type":"ScholarlyArticle","title":"BDI Agent Architectures: A Survey","authors":[{"name":"Lavindra de Silva","slug":"lavindra-de-silva","given":"Lavindra","family":"de Silva","affiliation":"University of Cambridge , Cambridge , UK"},{"name":"Felipe Meneguzzi","slug":"felipe-meneguzzi","given":"Felipe","family":"Meneguzzi","affiliation":"Pontifical Catholic University of Rio Grande do Sul , Porto Alegre , Brazil"},{"name":"Brian Logan","slug":"brian-logan","given":"Brian","family":"Logan","affiliation":"University of Nottingham , Nottingham , UK"}],"abstract":"The BDI model forms the basis of much of the research on symbolic models of agency and agent-oriented software engineering. While many variants of the basic BDI model have been proposed in the literature, there has been no systematic review of research on BDI agent architectures in over 10 years. In this paper, we survey the main approaches to each component of the BDI architecture, how these have been realised in agent programming languages, and discuss the trade-offs inherent in each approach.","doi":"10.24963/ijcai.2020/684","url":"https://ijcai.org/proceedings/2020/684","pdf":"https://ijcai.org/proceedings/2020/0684.pdf","markdown":"https://ijcai.org/proceedings/2020/684.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/684","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":684,"pages":{"first":4914,"last":4921},"keywords":["Agent-based and Multi-agent Systems: general"],"videos":[],"references":[{"position":1,"raw":"[Alechina et al., 2006] Natasha Alechina, Rafael Bordini, Jomi Hübner, Mark Jago, and Brian Logan. 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