Convex relaxations have been instrumental in solvability of constraint satisfaction problems (CSPs), as well as in the three different generalisations of CSPs: valued CSPs, infinite-domain CSPs, and most recently promise CSPs. In this work, we extend an existing tractability result to the three generalisations of CSPs combined: We give a sufficient condition for the combined basic linear programming and affine integer programming relaxation for exact solvability of promise valued CSPs over infinite-domains. This extends a result of Brakensiek and Guruswami [SODA'20] for promise (non-valued) CSPs (on finite domains).
翻译:稳妥的放松有助于制约性满意度问题(CSPs)的可溶性,也有利于CSPs的三个不同的概括性:有价值的CSPs、无限域CSPs和最近许诺的CSPs。 在这项工作中,我们将现有的可移性结果扩大到CSPs的三个概括性:我们为基本线性方案编制和近似整形方案编制的合并性放松提供了充分的条件,使具有价值的CSPs的允诺在无限域上的准确溶性。这延伸了Brakenseek和Guruswami(SODA'20)的允诺(无价值) CSPs(有限域)的结果。