An efficient consistency algorithm for the Temporal Constraint Satisfaction Problem

Authors:
Berthe Y. Choueiry;Lin Xu
Affiliations:
Constraint Systems Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln, USA E-mail: {choueiry,lxu}@cse.unl.edu (Correspond. 256 Avery Hall, Lincoln, NE, 6858 ...;Constraint Systems Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln, USA E-mail: {choueiry,lxu}@cse.unl.edu
Venue:
AI Communications - Spatial and Temporal Reasoning
Year:
2004

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Abstract

Dechter et al. [5] proposed solving the Temporal Constraint Satisfaction Problem (TCSP) by modeling it as a meta-CSP, which is a finite CSP with a unique global constraint. The size of this global constraint is exponential in the number of time points in the original TCSP, and generalized-arc consistency is equivalent to finding the minimal network of the TCSP, which is NP-hard. We introduce ▵AC, an efficient consistency algorithm for filtering the meta-CSP. This algorithm significantly reduces the domains of the variables of the meta-CSP without guaranteeing arc-consistency. We use ▵AC as a preprocessing step to solving the meta-CSP. We show experimentally that it dramatically reduces the size of a meta-CSP and significantly enhances the performance of search for finding the minimal network of the corresponding TCSP.