Exploiting Treewidth for Projected Model Counting and Its Limits.

Lecture Notes in Computer Science(2018)

引用 31|浏览53
暂无评分
摘要
In this paper, we introduce a novel algorithm to solve projected model counting (PMC). PMC asks to count solutions of a Boolean formula with respect to a given set of projected variables, where multiple solutions that are identical when restricted to the projected variables count as only one solution. Our algorithm exploits small treewidth of the primal graph of the input instance. It runs in time O(2(2k+4) n(2)) where k is the treewidth and n is the input size of the instance. In other words, we obtain that the problem PMC is fixed-parameter tractable when parameterized by treewidth. Further, we take the exponential time hypothesis (ETH) into consideration and establish lower bounds of bounded treewidth algorithms for PMC, yielding asymptotically tight runtime bounds of our algorithm.
更多
查看译文
关键词
Parameterized algorithms,Tree decompositions,Multi-pass dynamic programming,Projected model counting,Propositional logic
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要