Coping with disjunctions in temporal constraint satisfaction problems

Authors:
Eddie Schwalb;Rina Dechter
Affiliations:
Department of Information and Computer Science, University of California, Irvine, CA;Department of Information and Computer Science, University of California, Irvine, CA
Venue:
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Year:
1993

Citing 8
Cited 0

A sufficient condition for backtrack-bounded search

Journal of the ACM (JACM)
Temporal data base management

Artificial Intelligence
Network-based heuristics for constraint-satisfaction problems

Artificial Intelligence
Enhancement schemes for constraint processing: backjumping, learning, and cutset decomposition

Artificial Intelligence
Temporal constraint networks

Artificial Intelligence - Special issue on knowledge representation
Effective solution of qualitative interval constraint problems

Artificial Intelligence
Reasoning about qualitative temporal information

Artificial Intelligence - Special volume on constraint-based reasoning
Maintaining knowledge about temporal intervals

Communications of the ACM

Quantified Score

Hi-index	0.00

Visualization

Abstract

Path-consistency algorithms, which are polynomial for discrete problems, are exponential when applied to problems involving quantitative temporal information. The source of complexity stems from specifying relationships between pairs of time points as disjunction of intervals. We propose a polynomial algorithm, called ULT, that approximates path-consistency in Temporal Constralllt Satisfaction Problems (TCSPs). We compare ULT empirically to path-consistency and directional path-consistency algorithms. When used as a preprocessing to backtracking, ULT is shown to be 10 times more effective then either DPC or PC-2.