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  • 标题:Revisiting Counting Solutions for the Global Cardinality Constraint
  • 本地全文:下载
  • 作者:Giovanni Lo Bianco ; Xavier Lorca ; Charlotte Truchet
  • 期刊名称:Journal of Artificial Intelligence Research
  • 印刷版ISSN:1076-9757
  • 出版年度:2019
  • 卷号:66
  • 页码:411-441
  • 出版社:American Association of Artificial
  • 摘要:Counting solutions for a combinatorial problem has been identified as an important concern within the Artificial Intelligence field. It is indeed very helpful when exploring the structure of the solution space. In this context, this paper revisits the computation process to count solutions for the global cardinality constraint in the context of counting-based search. It first highlights an error and then presents a way to correct the upper bound on the number of solutions for this constraint.
  • 其他摘要:Counting solutions for a combinatorial problem has been identified as an important concern within the Artificial Intelligence field. It is indeed very helpful when exploring the structure of the solution space. In this context, this paper revisits the computation process to count solutions for the global cardinality constraint in the context of counting-based search. It first highlights an error and then presents a way to correct the upper bound on the number of solutions for this constraint.
  • 关键词:constraint programming;heuristics;counting;global cardinality
  • 其他关键词:constraint programming;heuristics;counting;global cardinality
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