1 research outputs found

    A Multivariate Complexity Analysis of Qualitative Reasoning Problems

    Full text link
    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 2O(nβ‹…log⁑n)2^{O(n \cdot \log n)} time, but single-exponential running times 2O(n)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 nn (e.g., the number of variables) and a coarse-grained parameter kk expected to be relatively small. We introduce the classes FPE and XE of problems solvable in f(k)β‹…2O(n)f(k) \cdot 2^{O(n)}, respectively f(k)nf(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 kk is solvable in 16kn16^{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 kk others is solvable in (2nk)2kβ‹…2n(2nk)^{2k} \cdot 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
    corecore