Non-deterministic read-once branching programs, also known as non-deterministic free binary decision diagrams (nFBDD), are a fundamental data structure in computer science for representing Boolean functions. In this paper, we focus on #nFBDD, the problem of model counting for non-deterministic read-once branching programs. The #nFBDD problem is #P-hard, and it is known that there exists a quasi-polynomial randomized approximation scheme for #nFBDD. In this paper, we provide the first FPRAS for #nFBDD. Our result relies on the introduction of new analysis techniques that focus on bounding the dependence of samples.


翻译:非确定性单次读取分支程序,亦称非确定性自由二元决策图(nFBDD),是计算机科学中用于表示布尔函数的基础数据结构。本文聚焦于#nFBDD问题,即非确定性单次读取分支程序的模型计数问题。#nFBDD问题属于#P难问题,已知存在针对该问题的拟多项式随机近似方案。本文首次提出了针对#nFBDD问题的完全多项式随机近似方案(FPRAS)。我们的研究成果依赖于引入新的分析技术,该技术着重于界定样本依赖性的边界。

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