Answer Set Programming (ASP) is a problem modeling and solving framework for several problems in KR with growing industrial applications. Also for studies of computational complexity and deeper insights into the hardness and its sources, ASP has been attracting researchers for many years. These studies resulted in fruitful characterizations in terms of complexity classes, fine-grained insights in form of dichotomy-style results, as well as detailed parameterized complexity landscapes. Recently, this lead to a novel result establishing that for the measure treewidth, which captures structural density of a program, the evaluation of the well-known class of normal programs is expected to be slightly harder than deciding satisfiability (SAT). However, it is unclear how to utilize this structural power of ASP. This paper deals with a novel reduction from SAT to normal ASP that goes beyond well-known encodings: We explicitly utilize the structural power of ASP, whereby we sublinearly decrease the treewidth, which probably cannot be significantly improved. Then, compared to existing results, this characterizes hardness in a fine-grained way by establishing the required functional dependency of the dependency graph's cycle length (SCC size) on the treewidth.
翻译:答案设置程序( ASP) 是一个在工业应用日益增长的 KR 中的问题模型和解决框架( ASP) 。 另外, 对于计算复杂性和对硬性及其来源的更深的洞察力的研究, ASP 多年来一直吸引研究人员。 这些研究在复杂分类、以二分法形式细化的洞察力以及详细的参数化复杂景观方面产生了富有成果的特征。 最近, 由此产生了一个新的结果, 确定测量树枝的树枝, 它捕捉到一个程序的结构密度, 对已知的普通程序类别的评估将比决定可作对称性( SAT) 略为难。 但是, 如何利用 ASP 的结构力量是不清楚的。 本文涉及从SAT 到正常的正常的ASP, 超越了众所周知的编码: 我们明确地利用了 ASP 的结构力量, 由此我们子线性地减少了树枝, 这也许无法大大改进。 然后, 与现有结果相比,, 通过确定所需的依赖性图周期( SC) 的功能依赖性大小, 将硬性描述成一个精确的硬性在树上。