On Mathematical Proving

P. Stefaneas, Ioannis M. Vandoulakis
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引用次数: 6

Abstract

Abstract This paper outlines a logical representation of certain aspects of the process of mathematical proving that are important from the point of view of Artificial Intelligence. Our starting-point is the concept of proof-event or proving, introduced by Goguen, instead of the traditional concept of mathematical proof. The reason behind this choice is that in contrast to the traditional static concept of mathematical proof, proof-events are understood as processes, which enables their use in Artificial Intelligence in such contexts, in which problem-solving procedures and strategies are studied. We represent proof-events as problem-centered spatio-temporal processes by means of the language of the calculus of events, which captures adequately certain temporal aspects of proof-events (i.e. that they have history and form sequences of proof-events evolving in time). Further, we suggest a “loose” semantics for the proof-events, by means of Kolmogorov’s calculus of problems. Finally, we expose the intented interpretations for our logical model from the fields of automated theorem-proving and Web-based collective proving.
论数学证明
摘要:本文概述了数学证明过程中某些方面的逻辑表示,这些方面从人工智能的角度来看是重要的。我们的出发点是Goguen引入的证明事件或证明的概念,而不是传统的数学证明概念。这种选择背后的原因是,与数学证明的传统静态概念相反,证明事件被理解为过程,这使得它们能够在人工智能中使用,在这种情况下,研究解决问题的过程和策略。我们通过事件演算的语言将证明事件表示为以问题为中心的时空过程,它充分捕捉了证明事件的某些时间方面(即它们具有历史和形式的证明事件序列随时间演变)。进一步,我们利用柯尔莫哥洛夫问题演算提出了证明事件的“松散”语义。最后,我们从自动定理证明和基于web的集体证明领域揭示了我们的逻辑模型的意图解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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