arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.14169cs.CCcs.DB
收藏

语义宽度与约束满足问题的固定参数可处理性

Semantic Width and the Fixed-Parameter Tractability of Constraint Satisfaction Problems

Hubie Chen, Georg Gottlob, Matthias Lanzinger, Reinhard Pichler

摘要:

约束满足问题(CSP)是统一处理各种突出AI任务的重要形式化框架,例如,着色或调度问题。解决CSP是,在一般情况下,已知的NP完全和固定参数的棘手时,其约束范围参数化。我们给出了这些类别的CSP的问题变得固定参数易处理的表征。我们的表征显着增加了CSP框架的效用,使之有可能决定通过其CSP配方的固定参数的问题的易处理性。我们进一步扩展我们的表征的联合查询,在数据库中的一个基本问题的评估。此外,我们提供了一些新的见解前沿的PTIME可解性的CSP。特别是,我们观察到,有界分数超树宽度比有界超树宽度更一般,只有类表现出某种类型的指数增长。所提出的工作解决了一个长期存在的开放问题,并为人工智能和数据库理论的复杂性研究提供了强大的新工具。

英文摘要:

Constraint satisfaction problems (CSPs) are an important formal framework for the uniform treatment of various prominent AI tasks, e.g., coloring or scheduling problems. Solving CSPs is, in general, known to be NP-complete and fixed-parameter intractable when parameterized by their constraint scopes. We give a characterization of those classes of CSPs for which the problem becomes fixed-parameter tractable. Our characterization significantly increases the utility of the CSP framework by making it possible to decide the fixed-parameter tractability of problems via their CSP formulations. We further extend our characterization to the evaluation of unions of conjunctive queries, a fundamental problem in databases. Furthermore, we provide some new insight on the frontier of PTIME solvability of CSPs. In particular, we observe that bounded fractional hypertree width is more general than bounded hypertree width only for classes that exhibit a certain type of exponential growth. The presented work resolves a long-standing open problem and yields powerful new tools for complexity research in AI and database theory.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑