教學大綱表 (113學年度 第2學期)
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課程名稱
Course Title		 (中文) 專家系統
(英文) Expert Systems 		開課單位
Departments		 資訊工程研究所
課程代碼
Course No.		 I5820
授課教師
Instructor		 林宜隆
學分數
Credit		 3.0 必/選修
core required/optional		 選修 開課年級
Level		 研究所
先修科目或先備能力(Course Pre-requisites)：會使用任何一種電腦程式語言 or Data Base System
課程概述與目標(Course Overview and Goals)：1. Know the capabilities of current technology in knowledge-based system(KBS) and expert systems(ES).
2. Be able to recognize what problems are appropriate for expert systems(ES/KBS).
3. Select an appropriate knowledge representation(KR) and reasoning method(IE), and anticipate potential difficulties in developing and introducing the expert systems(ES/KBS).
教科書(Textbook) 1.Expert Systems : Principles and Programming, 4th Edition
by Joseph Giarratano, and Gary Riley, 2007
2.Principles of Expert Systems by Peter J.F. Lucas & Linda C. van der Gaag 1991
3.Expert Systems: Design, Applications and Technology
作者 Darrel Ryan (Editor) Publication date： September 1, 2017
參考教材(Reference)
課程大綱 Syllabus 學生學習目標
Learning Objectives		 單元學習活動
Learning Activities		 學習成效評量
Evaluation		 備註
Notes
序
No.		 單元主題
Unit topic		 內容綱要
Content summary
1 INTRODUCTION TO EXPERT SYSTEMS 1. What Is an Expert System?
2. Advantages of Expert Systems
3. Expert Systems Applications and Domains 		1. understand what is an expert system.
2. understand the advantages of expert systems.
3. understand the applications of expert systems.		 討論
講授
 		問答
 		 
2 KNOWLEDGE REPRESENTATION (I) 1. The Meaning of Knowledge
2. Production rules
3. Semantic Nets
4. Object-Attribute-Value Triples
5. Frames
6. Clips Expert Systems 		1. Understand the different types of knowledge representation
2. Practice production rules in Clips expert system		 討論
講授
 		問答
 		 
3 KNOWLEDGE REPRESENTATION (II) 1. The Meaning of Knowledge
2. Production rules
3. Semantic Nets
4. Object-Attribute-Value Triples
5. Frames
6. Clips Expert Systems 		1. Understand the different types of knowledge representation
2. Practice production rules in Clips expert system		 討論
講授
 		問答
 		 
4 INTRODUCTION TO ES Tools 1. Facts, Adding and Removing Facts.
2. The Components of a Rule
3. Using Multiple Rules 		1. understand how to represent facts in ES tools.
2. understand how to represent rules in ES tools.
3. understand how to start, run and exit ES tools.		 講授
實作
 		問答
 		 
5 INFERENCE ENGINE (I) 1. State and Problem Spaces
2. Rules of Inference
3. Forward and Backward Chaining 		1. understand the components of inference engines.
2. understand how inference engines work.
3. understand how the inference engine of Clipse expert system		 講授
實作
 		問答
 		 
6 INFERENCE ENGINE (II) 1. State and Problem Spaces
2. Rules of Inference
3. Forward and Backward Chaining 		1. understand the components of inference engines.
2. understand how inference engines work.
3. understand how the inference engine of Clipse expert system		 講授
實作
 		問答
 		 
7 Rule-Based Expert Systems 1. Variables in Rule-Based Expert Systems.
2. Fact Addresses
3. Single-Field Wildcards
4. Multifield Wildcards and Variables
5. Field Constraints 		1. understand the constructs using inRule-Based Expert Systems.
2. understand howRule-Based Expert Systems in ES tools.		 討論
講授
 		問答
 		 
8 Frame-Based Expert Systems 1. Variables in Frame-Based Expert Systems.
2. Fact Addresses
3. Single-Field Wildcards
4. Multifield Wildcards and Variables
5. Field Constraints 		1. understand the constructs using in Frame-Based Expert Systems.
2. understand how Frame-Based Expert Systems in ES tools.		 討論
講授
 		問答
 		 
9 期中評量 期中評量 期中評量  
10 Reasoning Under Uncertainty (I) 1. Uncertainty
2. Compound Probabilities
3. Conditional Probabilities
4. Uncertainty in Inference Chains
5. The Combination of Evidence 		1. understand how to represent uncertainty in expert systems.
2. understand how to use uncertainty in Clips.		 討論
實作
 		報告
 		 
11 Reasoning Under Uncertainty (II) 1. Uncertainty
2. Compound Probabilities
3. Conditional Probabilities
4. Uncertainty in Inference Chains
5. The Combination of Evidence 		1. understand how to represent uncertainty in expert systems.
2. understand how to use uncertainty in Clips.		 討論
講授
 		問答
 		 
12 Fuzzy expert systems 1. Salience
2. Phases and Control Facts
3. Modules and Execution Control
4. Fuzzy expert systems 		1. understand how to prioritize rules.
2. understand how to group knowledge using module
3. understand Fuzzy expert systems		 討論
講授
 		問答
 		 
13 EFFICIENCY IN RULE-BASED LANGUAGES (I) 1. The Rete Pattern-Matching Algorithm
2, The Pattern Network
3. The Join Network 		1. understand the internal architecture of Clips
2. understand how rules are internally reorganized in Rete network.
3. understand the pattern matching process.		 討論
講授
 		問答
 		 
14 EFFICIENCY IN RULE-BASED LANGUAGES (II) 1. The Rete Pattern-Matching Algorithm
2, The Pattern Network
3. The Join Network 		1. understand the internal architecture of Clips
2. understand how rules are internally reorganized in Rete network.
3. understand the pattern matching process.		 討論
講授
 		報告
 		 
15 DESIGN OF EXPERT SYSTEMS 1. Selecting the Appropriate Problem
2. Stages in the Development of an Expert System
3. The Expert System Life Cycle 		1. understand the the software engineering of the Development of an Expert System.
2. write a simple expert system.		 討論
講授
實作
 		報告
 		 
16 EXPERT SYSTEM DESIGN EXAMPLES (I) Demo ES/Applications of Expert Systems(含期末評量) 1. Certainty Factors
2. Decision Trees
3. Backward Chaining
4. A Monitoring Problem
5. Applications of Expert Systems 		1. understand how to represent uncertainty in Clips.
2. understand how to reasoning with uncertainty.
3. understand learning in Clips
4. understand how to support backward chaining.
5.understand Applications of Expert Systems		 討論
講授
實作
 		報告
 		期末評量  
17 彈性教學(線上專題報告) 線上專題報告(個案研究及補充資料) 期末專題線上報告(個案研究) 討論
個案研究
 		報告
彈性教學
 		彈性教學(線上專題報告及補充資料)  
18 彈性教學(線上專題報告) 線上專題報告(個案研究及補充資料) 期末專題線上報告(個案研究) 討論
個案研究
 		報告
彈性教學
 		彈性教學(線上專題報告及補充資料)  
彈性教學週活動規劃
序
No.		 實施期間
Period		 實施方式
Content		 教學說明
Teaching instructions		 彈性教學評量方式
Evaluation		 備註
Notes
1 起:2024-06-10 迄:2024-06-21 5.小專題 Project 期末線上專題報告(個案研究) 實務操作分享與案例演練 期末報告及練習 彈性教學 (線上專題報告及補充資料) 彈性教學 (線上專題報告及補充資料)


教學要點概述：
1.自編教材 Handout by Instructor：
■ 1-1.簡報 Slids
■ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
■ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
■ 3.教科書作者提供 Textbook

成績考核 Performance Evaluation： 期末考：25%   期中考：25%   問答：10%   報告：15%   彈性教學：10%   平時考：15%  

教學資源(Teaching Resources)：
■ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)
課程網站(Website)：TTU 網路大學http://elearn.ttu.edu.tw
扣考規定：https://curri.ttu.edu.tw/p/412-1033-1254.php