Abstract
The Adaptive Constraint Engine (ACE) seeks to automate the application of constraint programming expertise and the extraction of domain-specific expertise. Under the aegis of FORR, an architecture for learning and problem-solving, ACE learns search-order heuristics from problem solving experience. This paper describes ACE.s approach, as well as new experimental results on specific problem classes. ACE is both a test-bed for CSP research and a discovery environment for new algorithms.
Cite
CITATION STYLE
Epstein, S. L., Freuder, E. C., Wallace, R., Morozov, A., & Samuels, B. (2002). The adaptive constraint engine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2470, pp. 525–540). Springer Verlag. https://doi.org/10.1007/3-540-46135-3_35
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