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Incremental qualitative temporal reasoning: Algorithms for the Point Algebra and the ORD-Horn class

Authors :
Gerevini, Alfonso
Source :
Artificial Intelligence. Aug2005, Vol. 166 Issue 1/2, p37-80. 44p.
Publication Year :
2005

Abstract

Abstract: In many applications of temporal reasoning we are interested in processing temporal information incrementally. In particular, given a set of temporal constraints (a temporal CSP) and a new constraint, we want to maintain certain properties of the extended temporal CSP (e.g., a solution), rather than recomputing them from scratch. The Point Algebra (PA) and the Interval Algebra (IA) are two well-known frameworks for qualitative temporal reasoning. The reasoning algorithms for PA and the tractable fragments of IA, such as Nebel and Bürckert''s maximal tractable class of relations (ORD-Horn), have originally been designed for “static” reasoning. In this paper, we study the incremental version of the fundamental reasoning problems in the context of these tractable classes. We propose a collection of new polynomial algorithms that can amortize their complexity when processing a sequence of input constraints to incrementally decide satisfiability, to maintain a solution, or to update the minimal representation of the CSP. Our incremental algorithms improve the total time complexity of using existing static techniques by a factor of or , where n is the number of the variables involved by the temporal CSP. An experimental analysis focused on constraints over PA confirms the computational advantage of our incremental approach. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
00043702
Volume :
166
Issue :
1/2
Database :
Academic Search Index
Journal :
Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
18127293
Full Text :
https://doi.org/10.1016/j.artint.2005.04.005