Fighting Perebor: New and Improved Algorithms for Formula and QBF Satisfiability

R. Santhanam
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引用次数: 87

Abstract

We investigate the possibility of finding satisfying assignments to Boolean formulae and testing validity of quantified Boolean formulae (QBF) asymptotically faster than a brute force search. Our first main result is a simple deterministic algorithm running in time $2^{n - \Omega(n)}$ for satisfiability of formulae of linear size in $n$, where $n$ is the number of variables in the formula. This algorithm extends to exactly counting the number of satisfying assignments, within the same time bound. Our second main result is a deterministic algorithm running in time $2^{n - \Omega(n/\log(n))}$ for solving QBFs in which the number of occurrences of any variable is bounded by a constant. For instances which are ``structured'', in a certain precise sense, the algorithm can be modified to run in time $2^{n - \Omega(n)}$. To the best of our knowledge, no non-trivial algorithms were known for these problems before. As a byproduct of the technique used to establish our first main result, we show that every function computable by linear-size formulae can be represented by decision trees of size $2^{n - \Omega(n)}$. As a consequence, we get strong super linear {\it average-case} formula size lower bounds for the Parity function.
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对抗缺陷:公式和QBF可满足性的新改进算法
我们研究了找到布尔公式的满意赋值和检验量化布尔公式(QBF)的渐近有效性的可能性,比暴力搜索更快。我们的第一个主要结果是一个简单的确定性算法运行在时间$2^{n - \Omega(n)}$中,用于$n$中线性大小公式的可满足性,其中$n$是公式中的变量数。该算法扩展到在相同的时间范围内精确计算满意分配的数量。我们的第二个主要结果是一个及时运行的确定性算法$2^{n - \Omega(n/\log(n))}$,用于求解QBFs,其中任何变量的出现次数都以常数为界。对于“结构化”的实例,在一定的精确意义上,算法可以修改以及时运行$2^{n - \Omega(n)}$。据我们所知,之前还没有针对这些问题的非平凡算法。作为用于建立我们第一个主要结果的技术的副产品,我们证明了每个可由线性大小公式计算的函数都可以由大小为$2^{n - \Omega(n)}$的决策树表示。因此,我们得到了奇偶{\it性函数的强超线性平均情况}公式大小下界。
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