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首页> 外文期刊>Annals of Mathematics and Artificial Intelligence >Solving the resolution-free SAT problem by submodel propagation in linear time
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Solving the resolution-free SAT problem by submodel propagation in linear time

机译:通过子模型在线性时间内的传播来解决无分辨率的SAT问题

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We present a method, called Unicorn-SAT, based on submodel propagation, which solves the resolution-free SAT problem in linear time. A formula is resolution-free if there are no two clauses which differ only in one variable, i.e., each clause is blocked for each literal in it. A resolution-free formula is satisfiable or it contains the empty clause. For such a restricted formula we can find a model in linear time by submodel propagation. Submodel propagation is hyper-unit propagation by a submodel generated from a minimal clause. Hyper-unit propagation is unit propagation simultaneously by literals, as unit clauses, of a partial assignment. We obtain a submodel, i.e., a part of the model, by negation of a neighbor-resolution-mate of a minimal clause, which is a clause with the smallest number of literals in the formula. We obtain a neighbor-resolution-mate of a clause by negating one literal in it. By submodel propagation we obtain a formula which has fewer variables and clauses and remains resolution-free. Therefore, we can obtain a model by joining the submodels while we perform submodel propagation recursively until the formula becomes empty.
机译:我们提出了一种基于子模型传播的名为Unicorn-SAT的方法,该方法解决了线性时间内无分辨率的SAT问题。如果没有两个仅在一个变量中不同的子句,则公式是无分辨率的,即每个子句都针对其中的每个文字被阻塞。无分辨率公式是可以满足的,或者包含空子句。对于这样一个受限制的公式,我们可以通过子模型传播在线性时间内找到一个模型。子模型传播是由最小子句生成的子模型的超单元传播。超单位传播是指通过部分分配的文字作为单位从句同时进行单位传播。通过否定最小子句的邻居分辨率匹配来获得子模型,即模型的一部分,最小子句是公式中文字数量最少的子句。我们通过否定子句中的一个字面值来获得该子句的邻居分辨率匹配。通过子模型传播,我们获得了一个具有较少变量和子句且保持无分辨率的公式。因此,在递归执行子模型传播直到公式变为空之前,我们可以通过加入子模型来获得模型。

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