Enhancement Schemes for Constraint Processing: Backjumping, Learning, and Cutset Decomposition

@article{Dechter1990EnhancementSF,
  title={Enhancement Schemes for Constraint Processing: Backjumping, Learning, and Cutset Decomposition},
  author={R. Dechter},
  journal={Artif. Intell.},
  year={1990},
  volume={41},
  pages={273-312}
}
  • R. Dechter
  • Published 1990
  • Mathematics, Computer Science
  • Artif. Intell.
  • Abstract Researchers in the areas of constraint satisfaction problems, logic programming, and truth maintenance systems have suggested various schemes for enhancing the performance of the backtracking algorithm. This paper defines and compares the performance of three such schemes: “backjumping,” “learning,” and “cycle-cutset.” The backjumping and the cycle-cutset methods work best when the constraint graph is sparse, while the learning scheme mostly benefits problem instances with dense… CONTINUE READING
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