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近来,在机器学习研究领域中,解释学习倍受重视,而其中心机制——解释推广却受限于一阶逻辑,为支持高阶对象和模态概念,本文介绍了两种扩充 Horn 逻辑表示域的方法,并通过例子说明了解释推广在扩充表示域中的实现。
Recently, in the field of machine learning, interpretation learning has received much attention, and its central mechanism - to explain the promotion is limited to first-order logic, in order to support high-order objects and modal concepts, this paper introduces two extended Horn logical representation Domain method, and illustrates by examples the implementation of the promotion in the extended representation domain.