逻辑与学习:从亚里士多德到神经网络

Vaishak Belle
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引用次数: 5

摘要

演绎和归纳法之间的紧张关系可能是哲学、认知和人工智能等领域最根本的问题。在本章中,我们调查了为逻辑和学习之间长期而深刻的联系提供证据的工作。在简短的历史前奏之后,我们的叙述是根据三股互动来构建的:逻辑对学习,机器学习对逻辑,逻辑对机器学习,但有很多重叠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Logic Meets Learning: From Aristotle to Neural Networks
The tension between deduction and induction is perhaps the most fundamental issue in areas such as philosophy, cognition and artificial intelligence. In this chapter, we survey work that provides evidence for the long-standing and deep connections between logic and learning. After a brief historical prelude, our narrative is then structured in terms of three strands of interaction: logic versus learning, machine learning for logic, and logic for machine learning, but with ample overlap.
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