| 當期課號 | 2923 | Course Number | 2923 |
|---|---|---|---|
| 授課教師 | 許志宇 | Instructor | HSU,CHIH YU |
| 中文課名 | 人工智慧 | Course Name | Artificial Intelligence |
| 開課單位 | 資訊與通訊系(四日)三A | Department | |
| 修習別 | 選修 | Required/Elective | Elective |
| 學分數 | 3 | Credits | 3 |
| 課程目標 | 本課程的主要宗旨將提供學生以對人工智慧的領域的實務理解。學生被教導發展基於規則和基於框架的專家系?，並設計一個模糊系?，探索人為神經系統網絡和實施一個????作為一種基因算法。學習本課程以後，學生將有人工智能的基本的概念。 | Objectives | The main objective of the course is to provide the students with praticial understanding of the field of computer intelligence. In the courses, the students is being teached to develop small rule-based and frame-based expert systems, to design a fuzzy system, to explore artificial neural networks, and to implement a simple problem as a genetic algorithm. After the courses, the students will have elementary concepts on artificial intelligence. |
| 教材 | 1.Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition) http://findbook.tw/book/9780321204660/basic 2.Russell & Norvig, Artificial intelligence -- A modern approach, Prentice Hall, 2nd ed., 2003, 東華書局代理. 3. Luger, Artificial intelligence -- Structures and strategies for complex problem solving, Addison Wesley, 4th ed., 2001, 東華書局代理. 4. 歐陽渭城 編譯，圖解人工智慧入門，初版，全華，民81年。 |
Teaching Materials | 1.Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition) http://findbook.tw/book/9780321204660/basic 2.Russell & Norvig, Artificial intelligence -- A modern approach, Prentice Hall, 2nd ed., 2003, 3. Luger, Artificial intelligence -- Structures and strategies for complex problem solving, Addison Wesley, 4th ed., |
| 成績評量方式 | 計畫報告 10% 作業+軟體 30% 期末考 30% 期中考 30% |
Grading | Project 1 20% Project 2 20% Midterm Exam 30% Final Exam 30% |
| 教師網頁 | http://www.cyut.edu.tw/~tccnchsu/ | ||
| 教學內容 | 1.基於知識的人工智慧系統介绍 2.基於規則的專家系统 3.基於規則的專家系统的不確定性管理 4.模糊的專家系统 5.基於框架的專家系统 6.人工神經網路 7.演化式計算 8.混合式智慧系統 9.知識工程和資料探勘 |
Syllabus | 1. Introduction to knowledge-based intelligent systems 2. Rule-based expert systems 3. Uncertainty management in rule-based expert systems 4. Fuzzy expert systems 5. Frame-based expert systems 6. Artificial neural networks 7. Evolutionary computation 8. Hybrid intelligent systems 9. Knowledge engineering and data mining |