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所在平台: Udemy |
课程主页: https://www.udemy.com/course/logic-in-artificial-intelligence/
课程评论：没有评论
课程名称：人工智能中的逻辑 课程概述：在本课程中，我们将了解谓词逻辑如何在构建人工智能系统中发挥作用。课程开始时，我们将探讨知识表示和命题逻辑，理解命题逻辑的语法和语义。接着，我们将扩展到谓词逻辑，充分理解谓词逻辑如何作为命题逻辑的一种推广形式。与命题逻辑相似，我们也将学习谓词逻辑的语法和语义。 随后，我们将致力于开发谓词逻辑的推理机制，并认识可应用于谓词的推理（推断）规则及其在功能上的差异。我们将讨论全称消去法与存在消去法之间的区别，以及我们在应用存在消去法时需要特别小心的原因和不同类型的存在消去技巧。 接下来，我们将学习如何将谓词表达式转换为规范形式，了解将谓词表达式转换为合取规范形式或析取规范形式的步骤。最后，我们将对归一化的谓词应用归结法，理解如何通过反驳进行推理及其含义。 本课程旨在帮助学习者掌握逻辑在人工智能中的关键作用和应用。
In this course we will understand how predicate logic helps in building AI systems. We will start by looking at knowledge representation and prepositional logic. We shall understand the syntax of propositional logic and the semantics behind it. Then we shall extend our understanding to predicate logic. We shall see how predicate logic a generalized form of prepositional logic is. Like prepositional logic we shall also see the syntax and semantics of predicate logic.Next, we shall work towards developing a reasoning mechanism for predicate logic and will also see what reasoning (inference) rules can be applied on predicate and how they differ in their functionality. We shall see how universal and existential elimination methods differ from each other. Why do we need to be extra cautious about existential elimination and what different types of existential elimination techniques are there.Then we shall look at how we can convert a predicate expression into canonical form. We will see what are the steps followed in converting a predicate expression into either conjunctive normal form or disjunctive normal form. Then we shall apply resolution onto the normalized predicates. Here we shall understand how reasoning can be applied through refutation and what are its implications.
