Answer Set Programming (ASP) is a declarative problem solving paradigm that can be used to encode a combinatorial problem as a logic program whose stable models correspond to the solutions of the considered problem. ASP has been widely applied to various domains in AI and beyond. The question "What can be said about stable models of a logic program from its static information?" has been investigated and proved useful in many circumstances. In this work, we dive into this direction more deeply by making the connection between a logic program and a Boolean network, which is a prominent modeling framework with applications to various areas. The proposed connection can bring the existing results in the rich history on static analysis of Boolean networks to explore and prove more theoretical results on ASP, making it become a unified and powerful tool to further study the static analysis of ASP. In particular, the newly obtained insights have the potential to benefit many problems in the field of ASP.

翻译：答案集编程（ASP）是一种声明式问题求解范式，可将组合问题编码为逻辑程序，其稳定模型对应于所考虑问题的解。ASP已广泛应用于人工智能及其他领域的多个方向。关于“如何从逻辑程序的静态信息推断其稳定模型的性质？”这一问题，已有研究证明其在诸多场景中具有重要价值。本研究通过建立逻辑程序与布尔网络之间的联系，对此方向进行更深入的探索。布尔网络作为一种重要的建模框架，已在多个领域得到应用。所提出的关联能够借助布尔网络静态分析领域丰富的历史成果，为ASP发掘并证明更多理论结果，使其成为进一步研究ASP静态分析的统一而强大的工具。特别地，新获得的见解有望对ASP领域的诸多问题产生积极影响。