{"type":"ScholarlyArticle","title":"On Robustness in Qualitative Constraint Networks","authors":[{"name":"Michael Sioutis","slug":"michael-sioutis","given":"Michael","family":"Sioutis","affiliation":"Otto-Friedrich-University Bamberg , WIAI , Bamberg , Germany"},{"name":"Zhiguo Long","slug":"zhiguo-long","given":"Zhiguo","family":"Long","affiliation":"Southwest Jiaotong University , SIST & IAI , Chengdu , China"},{"name":"Tomi Janhunen","slug":"tomi-janhunen","given":"Tomi","family":"Janhunen","affiliation":"Tampere University , ICT , Tampere , Finland"}],"abstract":"We introduce and study a notion of robustness in\r\nQualitative Constraint Networks (QCNs), which\r\nare typically used to represent and reason about \r\nabstract spatial and temporal information. In \r\nparticular, given a QCN, we are interested in obtaining \r\na robust qualitative solution, or, a robust scenario of\r\nit, which is a satisfiable scenario that has a higher\r\nperturbation tolerance than any other, or, in other\r\nwords, a satisfiable scenario that has more chances\r\nthan any other to remain valid after it is altered.\r\nThis challenging problem requires to consider the\r\nentire set of satisfiable scenarios of a QCN, whose\r\nsize is usually exponential in the number of constraints \r\nof that QCN; however, we present a first algorithm \r\nthat is able to compute a robust scenario of a QCN \r\nusing linear space in the number of constraints. \r\nPreliminary results with a dataset from the\r\njob-shop scheduling domain, and a standard one,\r\nshow the interest of our approach and highlight the\r\nfact that not all solutions are created equal.","doi":"10.24963/ijcai.2020/251","url":"https://ijcai.org/proceedings/2020/251","pdf":"https://ijcai.org/proceedings/2020/0251.pdf","markdown":"https://ijcai.org/proceedings/2020/251.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/251","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":"Knowledge Representation and Reasoning","track":"Main track","number":251,"pages":{"first":1813,"last":1819},"keywords":["Knowledge Representation and Reasoning: Qualitative, Geometric, Spatial, Temporal Reasoning"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/24758/file_24758.m3u8","length_sec":285,"provider":"hls"}],"references":[{"position":1,"raw":"[Allen, 1983] James F. 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