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Little Engines of Proof

机译:证明的一点发动机

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摘要

The automated construction of mathematical proof is a basic activity in computing. Since the dawn of the field of automated reasoning, there have been two divergent schools of thought. One school, best represented by Alan Robinson's resolution method, is based on simple uniform proof search procedures guided by heuristics. The other school, pioneered by Hao Wang, argues for problem-specific combinations of decision and semi-decision procedures. While the former school has been dominant in the past, the latter approach has greater promise. In recent years, several high quality inference engines have been developed, including propositional satisfiability solvers, ground decision procedures for equality and arithmetic, quantifier elimination procedures for integers and reals, and abstraction methods for finitely approximating problems over infinite domains. We describe some of these "little engines of proof" and a few of the ways in which they can be combined. We focus in particular on combining different decision procedures for use in automated verification.
机译:数学证据的自动建设是计算中的基本活动。自自动推理领域的曙光以来,有两所不同的思想学校。一所学校,最好由Alan Robinson的分辨率方法代表,是基于启发式的简单统一证明搜索程序。其他学校由郝王开创,争论了特定于问题的决策和半决定程序的组合。虽然过去的学校过去一直占主导地位,但后一种方法有更大的承诺。近年来,已经开发了几个高质量的推理引擎,包括命题可靠性求解器,平等和算术,量化的地面决策程序,用于整数和实际的算法,以及用于在无限域的有限近似问题的抽象方法。我们描述了一些这些“少量发动机的证据”和一些可以组合的方式。我们特别关注不同决策程序以便在自动验证中使用。

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