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Beating Exhaustive Search for Quantified Boolean Formulas and Connections to Circuit Complexity

机译:击败穷举搜索量化布尔公式和电路复杂度的连接

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摘要

We study algorithms for the satisfiability problem for quantified Boolean formulas (QBFs), and consequences of faster algorithms for circuit complexity.We show that satisfiability of quantified 3-CNFs with m clauses, n variables, and two quantifier blocks (one existential block and one universal) can be solved deterministically in time . poly(m). For the case of multiple quantifier blocks (alternations), we show that satisfiability of quantified CNFs of size poly(n) on n variables with q quantifier blocks can be solved in 2n−n1/(q + 1)· poly(n) time by a zero-error randomized algorithm. These are the first provable improvements over brute force search in the general case, even for quantified polynomial-sized CNFs with two quantifier blocks.A second zero-error randomized algorithm solves QBF on circuits of size s in 2n–Ω(q) · poly(s) time when the number of quantifier blocks is q.We complement these algorithms by showing that improvements on them would imply new circuit complexity lower bounds. For example, if satisfiability of quantified CNF formulas with n variables, poly(n) size and at most q quantifier blocks can be solved in time 2n–nwq (1/q) then the complexity class NEXP does not have O(log n) depth circuits of polynomial size. Furthermore, solving satisfiability of quantified CNF formulas with n variables, poly(n) size and O(log n) quantifier blocks in time 2n–w(log (n)) time would imply the same circuit complexity lower bound. The proofs of these results proceed by establishing strong relationships between the time complexity of QBF satisfiability over CNF formulas and the time complexity of QBF satisfiability over arbitrary Boolean formulas.
机译:我们研究了量化布尔公式(QBF)的可满足性问题的算法,以及电路复杂度更快的算法的结果。我们证明了具有m个子句,n个变量和两个量化器块(一个存在性块和一个量化器块)的量化3-CNF的可满足性通用性)可以及时确定地解决。 poly(m)。对于多个量词块(交替),我们证明可以在2n-n1 /(q + 1)·poly(n)时间内解决n个变量上q个量词的大小poly(n)的量化CNF的可满足性通过零误差随机算法。这些是在一般情况下对蛮力搜索的第一个可证明的改进,即使对于具有两个量词块的量化多项式大小的CNF也是如此。第二种零误差随机算法解决了2n–Ω(q)·s大小的电路上的QBF (s)量化块的数量为q的时间。我们通过证明对这些算法的改进将暗示新的电路复杂性下限来对这些算法进行补充。例如,如果可以在2n–nwq(1 / q)的时间内求解具有n个变量,poly(n)大小和最多q个量词块的量化CNF公式的可满足性,则复杂度类NEXP不会具有O(log n)多项式大小的深度电路。此外,在2n–w(log(n))时间内用n个变量,poly(n)大小和O(log n)量词块求解量化CNF公式的可满足性将意味着相同的电路复杂度下限。这些结果的证明是通过在CNF公式上的QBF可满足性的时间复杂度与任意布尔公式上的QBF可满足性的时间复杂性之间建立牢固的关系来进行的。

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