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所在平台: Udemy |
课程主页: https://www.udemy.com/course/foundations-of-ai-search-algorithms/
课程评论：没有评论
**人工智能基础：搜索算法** 本课程面向所有对投身人工智能领域感兴趣的学习者。课程旨在打下坚实的基础，深入探讨人工智能的基本概念，包括其定义、不同学派的思想，以及图灵关于计算思维的观点。 课程将重点讲解图的意义及其在问题表示中的应用。其核心内容是搜索算法，我们将学习计算机如何在庞大的解空间中寻找解决方案，包括无信息搜索和有信息搜索算法。有信息搜索算法在机器人学、导航系统、游戏设计等领域有着广泛的应用。 为解决搜索算法中的问题，课程还将介绍局部搜索算法，最终引向优化问题。在局部搜索中，我们将学习爬山算法及其局限性。 总而言之，本课程将解答学习者关于人类智能与机器智能根本区别的疑问。
This course is designed for all enthusiasts who are interested for a career in Artificial Intelligence. The main objective of this course is to give a solid foundation of the good old Artificial Intelligence concepts which includes the definition of Artificial Intelligence, different schools of Thought, a tinge of Sir Alan Turing's thoughts about Computational Thinking. As we progress into the course, we will try to understand the significance of graphs and how any problem can be represented as a Graph. At the heart of this course is Search Algorithms, we will have a look at methods that allow computers to search for solution in a huge solution space. In that pursuit, we will work with Uninformed Search and Informed Search Algorithms. Informed Search algorithms have their foot print in Robotics, Navigation systems, designing games and many more. Course is incomplete if we leave with informed search, to counter the problems of search algorithms, we will look into local search which will eventually land in Optimization. In local search, we will work with Hill climbing algorithms along with their disadvantages. To sum up, this course gives answers to questions raised by students who want to explore the fundamentals difference between human intelligence and machine intelligence.
