Subdefinite models as a variety of constraint programming

V. Telerman, Dmitry Ushakov
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引用次数: 15

Abstract

This paper describes subdefinite models as a variety of constraint satisfaction problems. The use of the method of subdefinite calculations makes it possible to solve overdetermined and underdetermined problems, as well as problems with uncertain, imprecise and incomplete data. Constraint propagation in all these problems is supported by a single data-driven inference algorithm. Several examples are given to show the capabilities of this approach for solving a wide class of problems.
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子集模型作为约束规划的多种形式
本文将亚确定模型描述为各种约束满足问题。利用亚定计算方法,可以解决超定和欠定问题,以及不确定、不精确和数据不完整的问题。所有这些问题的约束传播都由单一的数据驱动推理算法支持。给出了几个例子来展示这种方法在解决广泛问题方面的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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