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docs/人工智能/CS188.en.md

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+# CS188: Introduction to Artificial Intelligence
+
+## Course Overview
+
+- University：UC Berkeley
+- Prerequisites：CS70
+- Programming Language：Python
+- Course Difficulty：🌟🌟🌟
+- Estimated Hours：50 hours
+
+This introductory artificial intelligence course at UC Berkeley provides in-depth and accessible course notes, making it possible to grasp the material without necessarily watching the lecture videos. The course follows the chapters of the classic AI textbook *Artificial Intelligence: A Modern Approach*, covering topics such as search pruning, constraint satisfaction problems, Markov decision processes, reinforcement learning, Bayesian networks, Hidden Markov Models, as well as fundamental concepts in machine learning and neural networks.
+
+The Fall 2018 version of the course offered free access to gradescope, allowing students to complete written assignments online and receive real-time assessment results. The course also includes 6 projects of high quality, featuring the recreation of the classic Pac-Man game. These projects challenge students to apply their AI knowledge to implement various algorithms, enabling their Pac-Man to navigate mazes, evade ghosts, and collect pellets.
+
+## Course Resources
+
+- Course Websites：[Fall 2022](https://inst.eecs.berkeley.edu/~cs188/fa22/)，[Fall 2018](https://inst.eecs.berkeley.edu/~cs188/fa18/index.html)
+- Course Videos：[Fall 2022](https://inst.eecs.berkeley.edu/~cs188/fa22/)，[Fall 2018](https://inst.eecs.berkeley.edu/~cs188/fa18/index.html)，with links to each lecture on the course website
+- Course Textbook：Artificial intelligence: A Modern Approach
+- Course Assignments：Online assessments for written assignments and projects, details available on the course website