Improving search using indexing: a study with temporal CSPs

Authors:
Nikos Mamoulis;Dimitris Papadias
Affiliations:
Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
Venue:
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Year:
1999

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Abstract

Most studies concerning constraint satisfaction problems (CSPs) involve variables that take values from small domains. This paper deals with an alternative form of temporal CSPs; the number of variables is relatively small and the domains are large collections of intervals. Such situations may arise in temporal databases where several types of queries can be modeled and processed as CSPs. For these problems, systematic CSP algorithms can take advantage of temporal indexing to accelerate search. Directed search versions of chronological backtracking and forward checking are presented and tested. Our results show that indexing can drastically improve search performance.