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Machine Learning Guidance for Connection Tableaux
Journal of Automated Reasoning ( IF 0.9 ) Pub Date : 2020-09-05 , DOI: 10.1007/s10817-020-09576-7
Michael Färber , Cezary Kaliszyk , Josef Urban

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:

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。
更新日期:2020-09-05
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