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A Multivariate Complexity Analysis of Qualitative Reasoning Problems
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Integrated Computer Systems. Linköping University, Faculty of Science & Engineering.
2022 (English)In: Proceedings of the 31st International Joint Conference on Artificial Intelligence, 2022, p. 1804-1810Conference paper, Published paper (Refereed)
Abstract [en]

Qualitative reasoning is an important subfield of artificial intelligence where one describes relationships with qualitative, rather than numerical, relations. Many such reasoning tasks, e.g., Allen's interval algebra, can be solved in 2^O(n*log n) time, but single-exponential running times 2^O(n) are currently far out of reach. In this paper we consider single-exponential algorithms via a multivariate analysis consisting of a fine-grained parameter n (e.g., the number of variables) and a coarse-grained parameter k expected to be relatively small. We introduce the classes FPE and XE of problems solvable in f(k)*2^O(n), respectively f(k)^n, time, and prove several fundamental properties of these classes. We proceed by studying temporal reasoning problems and (1) show that the partially ordered time problem of effective width k is solvable in 16^{kn} time and is thus included in XE, and (2) that the network consistency problem for Allen's interval algebra with no interval overlapping with more than k others is solvable in (2nk)^{2k}*2^n time and is included in FPE. Our multivariate approach is in no way limited to these to specific problems and may be a generally useful approach for obtaining single-exponential algorithms.

Place, publisher, year, edition, pages
2022. p. 1804-1810
Keywords [en]
Constraint Satisfaction and Optimization: Constraint Satisfaction
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-198450DOI: 10.24963/ijcai.2022/251OAI: oai:DiVA.org:liu-198450DiVA, id: diva2:1804538
Conference
International Joint Conference on Artificial Intelligence, Messe Wien, Vienna, Austria, July 23-29, 2022
Available from: 2023-10-13 Created: 2023-10-13 Last updated: 2023-10-18Bibliographically approved

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Eriksson, LeifLagerkvist, Victor

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  • apa
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