论文标题
推进懒惰的ASP求解技术 - 重新启动，节省相位，启发式方法等等
Advancing Lazy-Grounding ASP Solving Techniques -- Restarts, Phase Saving, Heuristics, and More
论文作者
论文摘要
答案集编程（ASP）是一种强大而表达的知识表示范式，具有大量基于逻辑的AI中的应用程序。但是，传统的地面和解决方法要求ASP程序进行前期接地，因此遭受了所谓的接地瓶颈（即，ASP程序很容易耗尽所有可用的内存，从而变得难以解决）。作为一种补救措施，已经开发了懒惰的ASP求解器，但是许多用于接地的ASP解决方案的最新技术尚未提供。在这项工作中，我们首次介绍了许多重要技术的懒惰环境，例如重新启动，储蓄，独立于域的启发式方法和学习的差异删除。此外，我们研究了它们的效果，一般而言，在某些情况下，在解决能力方面有很大的改善，并且在某些情况下发现了负面影响，这表明需要解决投资组合解决方案，如其他求解器所知。正在考虑在TPLP中接受。
Answer-Set Programming (ASP) is a powerful and expressive knowledge representation paradigm with a significant number of applications in logic-based AI. The traditional ground-and-solve approach, however, requires ASP programs to be grounded upfront and thus suffers from the so-called grounding bottleneck (i.e., ASP programs easily exhaust all available memory and thus become unsolvable). As a remedy, lazy-grounding ASP solvers have been developed, but many state-of-the-art techniques for grounded ASP solving have not been available to them yet. In this work we present, for the first time, adaptions to the lazy-grounding setting for many important techniques, like restarts, phase saving, domain-independent heuristics, and learned-clause deletion. Furthermore, we investigate their effects and in general observe a large improvement in solving capabilities and also uncover negative effects in certain cases, indicating the need for portfolio solving as known from other solvers. Under consideration for acceptance in TPLP.
