Arc and path consistence revisited
Artificial Intelligence
Artificial Intelligence
Effective solution of qualitative interval constraint problems
Artificial Intelligence
Reasoning about qualitative temporal information
Artificial Intelligence - Special volume on constraint-based reasoning
Arc-consistency and arc-consistency again
Artificial Intelligence
Combining qualitative and quantitative constraints in temporal reasoning
Artificial Intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
The design and experimental analysis of algorithms for temporal reasoning
Journal of Artificial Intelligence Research
Using inference to reduce arc consistency computation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A simple way to improve path consistency processing in interval algebra networks
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Dynamic CSPs for Interval-Based Temporal Reasoning
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
Reasoning with Numeric and Symbolic Time Information
Artificial Intelligence Review
AI Communications - Special issue on: Spatial and temporal reasoning
Maintaining global consistency of temporal constraints in a dynamic environment
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
AI Communications - Spatial and Temporal Reasoning
International Journal of Knowledge-based and Intelligent Engineering Systems
Dynamic arc consistency for CSPs
International Journal of Knowledge-based and Intelligent Engineering Systems
Conditional and composite temporal CSPs
Applied Intelligence
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Many temporal applications like planning and schedulingcan be viewed as special cases of the numeric and symbolic temporalconstraint satisfaction problem. Thus we have developed a temporalmodel, TemPro, based on the interval Algebra, to express suchapplications in term of qualitative and quantitative temporalconstraints. TemPro extends the interval algebra relations ofAllen to handle numeric information. To solve a constraint satisfactionproblem, different approaches have been developed. These approachesgenerally use constraint propagation to simplify the originalproblem and backtracking to directly search for possible solutions.The constraint propagation can also be used during the backtrackingto improve the performance of the search. The objective of thispaper is to assess different policies for finding if a TemPronetwork is consistent. The main question we want to answer hereis ’’how much constraint propagation is useful‘‘ for findinga single solution for a TemPro constraint graph. For this purpose,we have experimented by randomly generating large consistentnetworks for which either arc and/or path consistency algorithms(AC-3, AC-7 and PC-2) were applied. The main result of this studyis an optimal policy combining these algorithms either at thesymbolic (Allen relation propagation) or at the numerical level.