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Temporal Constraints: A Survey

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Abstract

Temporal Constraint Satisfaction is an information technology useful for representing and answering queries about temporal occurrences and temporal relations between them. Information is represented as a Constraint Satisfaction Problem (CSP) where variables denote event times and constraints represent the possible temporal relations between them. The main tasks are two: (i) deciding consistency, and (ii) answering queries about scenarios that satisfy all constraints. This paper overviews results on several classes of Temporal CSPs: qualitative interval, qualitative point, metric point, and some of their combinations. Research has progressed along three lines: (i) identifying tractable subclasses, (ii) developing exact search algorithms, and (iii) developing polynomial-time approximation algorithms. Most available techniques are based on two principles: (i) enforcing local consistency (e.g. path-consistency) and (ii) enhancing naive backtracking search.

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Authors and Affiliations

  1. Information and Computer Science, University of California, Irvine, USA

    Eddie Schwalb

  2. Institute for Research in Artificial Intelligence (IIIA)–CSIC, Catalonia, Spain

    Lluís Vila

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  1. Eddie Schwalb
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  2. Lluís Vila
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Schwalb, E., Vila, L. Temporal Constraints: A Survey. Constraints 3, 129–149 (1998). https://doi.org/10.1023/A:1009717525330

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