Three years ago, Philip Zucker posted an attempt to use answer set programming (ASP) for term extraction from e-graphs Although the task is NP-hard and ASP offers a natural modelling of e-graph terms, the initial attempt did not yield convincing results. From the aspect of practical ASP users, we first pinpoint the way to make ASP work and work well on the task of e-graph extraction. The initial results show the naïve ASP encoding is comparable on efficiency to the well-optimised ILP-based exact DAG extraction in the extraction-gym, and find several extra optimal extraction on the complex instances. This leads us to a further agenda: with the "better together of egg+Datalog", is there a better "better together" by having ASP as a more powerful Datalog? We discuss the potential benefit from each other.

翻译：三年前，Philip Zucker曾尝试使用回答集编程（ASP）从e图中抽取项。尽管该任务是NP难的，且ASP为e图项的建模提供了自然的范式，但其初步尝试并未取得令人信服的结果。从实际ASP用户的角度出发，我们首先明确了使ASP在e图抽取任务中有效运行并取得良好效果的方法。初步结果表明，朴素的ASP编码在效率上与抽取健身房中基于ILP的精确有向无环图（DAG）抽取优化方法相当，并在复杂实例上发现了若干额外的最优抽取结果。这引导我们提出进一步议程：既然"egg与Datalog的协同增强"已显成效，那么将ASP作为更强大的Datalog是否可能实现更优的协同增效？我们探讨了双方相互裨益的潜在可能性。