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所在平台: Udemy |
课程主页: https://www.udemy.com/course/artificial-intelligence-algorithms/
课程评论：没有评论
**课程名称：** 人工智能算法 **课程概述：** 本课程将深入探讨人工智能算法的原理与应用。我们将从经典的图遍历算法——广度优先搜索（BFS）和深度优先搜索（DFS）入手，逐步建立对更智能搜索方法的理解。 课程将重点介绍： * **以统一代价搜索（Uniform Cost Search）为基础**：引入边的权重概念，并在此基础上对其进行改进，应用启发式估计。 * **爬山算法（Hill Climbing Algorithm）**：从不同的视角探索解决问题的方法。 * **多解优化**：学习如何从多个可用解决方案中找出最优解。 * **博弈论中的算法**： * **零和博弈（Zero-Sum Games）**：理解其运作机制。 * **游戏树的优化**：通过剪枝技术（如浅剪枝和深剪枝）来优化博弈树的搜索过程。 * **Min-Max 算法**：学习其工作原理，并探讨如何通过剪枝来对其进行优化。 通过本课程的学习，您将掌握人工智能领域核心算法的设计与应用，为解决复杂问题提供坚实的技术基础。
In this course we will understand how artificial intelligence algorithms work. We will start by looking at traditional graph traversal algorithms i.e. breath first search and depth first search. From there will build our understanding of making searches more intelligent. Specifically, we will be looking at uniform cost search where we shall introduce weights to the edges and then shall modify this algorithm by applying estimates to it. We shall also look at hill climbing algorithm which is has a different perspective of searching the desired goal.We will then look at how we can apply the concepts learnt into a new perspective of problem solving where if we have multiple available solutions then the algorithm should be able to find out which among them is the best solution.We shall look at game playing where we will see show zero sum games work and how we can optimize these games by pruning a partial game tree. We shall first look at the working of a procedure called max-min algorithm and then in order to optimize this procedure, we shall apply pruning to it. We will look at what is shallow pruning and deep pruning and how take affect the game tree.
