{"type":"ScholarlyArticle","title":"Efficiently Characterizing Non-Redundant Constraints in Large Real World Qualitative Spatial Networks","authors":[{"name":"Michael Sioutis","slug":"michael-sioutis","given":"Michael","family":"Sioutis","affiliation":""},{"name":"Sanjiang Li","slug":"sanjiang-li","given":"Sanjiang","family":"Li","affiliation":""},{"name":"Jean-François Condotta","slug":"jean-francois-condotta","given":"Jean-François","family":"Condotta","affiliation":""}],"abstract":"RCC8 is a constraint language that serves for qualitative spatial representation and reasoning by encoding the topological relations between spatial entities. We focus on efficiently characterizing non-redundant constraints in large real world RCC8 networks and obtaining their prime networks. For a RCC8 network N a constraint is redundant, if removing that constraint from N does not change the solution set of N. A prime network of N is a network which contains no redundant constraints, but has the same solution set as N. We make use of a particular partial consistency, namely, G-path consistency, and obtain new complexity results for various cases of RCC8 networks, while we also show that given a maximal distributive subclass for RCC8 and a network N defined on that subclass, the prunning capacity of G-path consistency and path consistency is identical on the common edges of G and the complete graph of N, when G is a triangulation of the constraint graph of N. Finally, we devise an algorithm based on G-path consistency to compute the unique prime network of a RCC8 network, and show that it significantly progresses the state-of-the-art for practical reasoning with real RCC8 networks scaling up to millions of nodes.","doi":null,"url":"https://ijcai.org/proceedings/2015/455","pdf":"https://ijcai.org/proceedings/2015/0455.pdf","markdown":"https://ijcai.org/proceedings/2015/455.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/455","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Special Track on Knowledge Representation and Reasoning","track":"Special Track on Knowledge Representation and Reasoning","number":455,"pages":{"first":3229,"last":3234},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}