Explanation in constraint satisfaction: A survey

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Dev Gupta, Sharmi
Genç, Begüm
O'Sullivan, Barry
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Much of the focus on explanation in the field of artificial intelligence has focused on machine learning methods and, in particular, concepts produced by advanced methods such as neural networks and deep learning. However, there has been a long history of explanation generation in the general field of constraint satisfaction, one of the AI's most ubiquitous subfields. In this paper we survey the major seminal papers on the explanation and constraints, as well as some more recent works. The survey sets out to unify many disparate lines of work in areas such as model-based diagnosis, constraint programming, Boolean satisfiability, truth maintenance systems, quantified logics, and related areas.
Artificial intelligence , AI , Constraint satisfaction , Boolean satisfiability
Dev Gupta, S., Genc, B. and O'Sullivan, B. (2021) 'Explanation in Constraint Satisfaction: A Survey', JCAI 2021: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, Canada. Virtual Event, 17-27 August, pp. 4400-4407. doi:10.24963/ijcai.2021/601
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