Answer set programming is a leading declarative constraint programming paradigm with wide use for complex knowledge-intensive applications. Modern answer set programming languages support many equivalent ways to model constraints and specifications in a program. However, so far answer set programming has failed to develop systematic methodologies for building representations that would uniformly lend well to automated processing. This suggests that encoding selection, in the same way as algorithm selection and portfolio solving, may be a viable direction for improving performance of answer-set solving. The necessary precondition is automating the process of generating possible alternative encodings. Here we present an automated rewriting system, the Automated Aggregator or AAgg, that given a non-ground logic program, produces a family of equivalent programs with complementary performance when run under modern answer set programming solvers. We demonstrate this behavior through experimental analysis and propose the system's use in automated answer set programming solver selection tools.

中文翻译：

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自动聚合器——用计数聚合重写

答案集编程是一种领先的声明式约束编程范式，广泛用于复杂的知识密集型应用程序。现代答案集编程语言支持许多对程序中的约束和规范进行建模的等效方法。然而，到目前为止，答案集编程未能开发出系统的方法来构建表示，这些方法可以统一地很好地用于自动化处理。这表明编码选择与算法选择和组合求解一样，可能是提高答案集求解性能的可行方向。必要的先决条件是自动化生成可能的替代编码的过程。在这里，我们提出了一个自动重写系统，自动聚合器或 AAgg，它给出了一个非地面逻辑程序，在现代答案集编程求解器下运行时，产生一系列具有互补性能的等效程序。我们通过实验分析证明了这种行为，并提出了该系统在自动答案集编程求解器选择工具中的使用。