2001/09/13 by Janet van der Linden, van der Linden, Janet
Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #Constraint Satisfaction and Optimization #D.3.2 #D3.3 #Data Management and Algorithms #FOS: Computer and information sciences #Programming Languages (cs.PL) #cs.AI #cs.PL
paper · pdf · doi:10.48550/arxiv.cs/0109014
11 pages. Proceedings ERCIM WG on Constraints (Prague, June 2001)
arxiv created 2001/09/13 · openalex publication_date 2001/09/13 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
The model of Dynamic Meta-Constraints has special activity constraints which can activate other constraints. It also has meta-constraints which range over other constraints. An algorithm is presented in which constraints can be assigned one of five different satisfaction values, which leads to the assignment of domain values to the variables in the CSP. An outline of the model and the algorithm is presented, followed by some initial results for two problems: a simple classic CSP and the Car Configuration Problem. The algorithm is shown to perform few backtracks per solution, but to have overheads in the form of historical records required for the implementation of state.