Explanation in constraint satisfaction: A survey

Dev Gupta, Sharmi; Genç, Begüm; O'Sullivan, Barry

Explanation in constraint satisfaction: A survey

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Published version

Date

2021-08-17

Authors

Dev Gupta, Sharmi

Genç, Begüm

O'Sullivan, Barry

Publisher

International Joint Conferences on Artificial Intelligence Organization

Published Version

10.24963/ijcai.2021/601

Abstract

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.

Keywords

Artificial intelligence , AI , Constraint satisfaction , Boolean satisfiability

Citation

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