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;Constraint Systems Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln
Venue:
AI Communications - Special issue on: 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-are consistency is equivalent to finding the minimal network of the TCSP, which is NP-hard. We introduce ΔAC, 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 rise ΔAC 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.