从查询中近似正确地学习Horn包络
Probably approximately correct learning of Horn envelopes from queries
摘要：
我们提出了一种算法，用于学习的任意域的霍恩包络使用的专家，或甲骨文，能够回答某些类型的查询这个域。来自形式概念分析的属性探索是解决这个问题的一个过程，但是在最坏的情况下，它可能要求的查询数量在所得到的Horn公式的大小上是指数级的。我们回顾了一个著名的多项式时间算法学习霍恩公式的成员资格和等价查询，并修改它，以获得一个多项式时间可能近似正确的算法学习任意域的霍恩包络。
英文摘要：
We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of queries about this domain. Attribute exploration from formal concept analysis is a procedure that solves this problem, but the number of queries it may ask is exponential in the size of the resulting Horn formula in the worst case. We recall a well-known polynomial-time algorithm for learning Horn formulas with membership and equivalence queries and modify it to obtain a polynomial-time probably approximately correct algorithm for learning the Horn envelope of an arbitrary domain.
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