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Solving equational problems efficiently

机译:有效地解决方程式问题

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Equational problems (i.e.: first-order formulae with quantifier prefix, whose only predicate symbol is syntactic equality) are an important tool in many areas of automated deduction. e.g.: restricting the set of ground instances of a clause via equational constraints allows the definition of stronger redundancy criteria and hence, in general, of more efficient theorem provers. Moreover, also the inference rules themselves can be restricted via constraints. In automated model building, equational problems play an important role both in the definition of an appropriate model representation and in the evaluation of clauses in such models. Also, many problems in the area of logic programming can be reduced to equational problem solving.
机译:方程问题(即:带量词前缀的一阶公式,其唯一的谓词是句法等式)是许多自动推论领域中的重要工具。例如:通过方程式约束来限制子句的基础实例集,可以定义更强的冗余标准,因此通常可以定义更有效的定理证明。此外,推理规则本身也可以通过约束来限制。在自动模型构建中,方程式问题在定义适当的模型表示形式以及评估此类模型中的子句中均扮演着重要角色。同样,可以将逻辑编程领域的许多问题简化为方程式问题求解。

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