Connection calculi allow for very compact implementations of goal-directed proof search. We give an overview of our work related to connection tableaux calculi: first, we show optimised functional implementations of connection tableaux proof search, including a consistent Skolemisation procedure for machine learning. Then, we show two guidance methods based on machine learning, namely reordering of proof steps with Naive Bayesian probabilities, and expansion of a proof search tree with Monte Carlo Tree Search.

中文翻译：

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连接表的机器学习指南

连接演算允许目标导向证明搜索的非常紧凑的实现。我们概述了与连接表演算相关的工作：首先，我们展示了连接表证明搜索的优化功能实现，包括用于机器学习的一致 Skolemisation 程序。然后，我们展示了两种基于机器学习的指导方法，即使用朴素贝叶斯概率重新排序证明步骤，以及使用蒙特卡罗树搜索扩展证明搜索树。