CCU Course Intro
Course Title (Chinese): 智慧型代理人系統 Teaching Unit: 電機工程研究所(Graduate Institute of Electrical Engineering)
Course Title (English) Intelligent Agent Systems Course Code 4156324_01
Lecturer: 劉立頌 (Alan Liu) Number of Credits 3
Mandatory/Elective Elective Year Graduate level
Prerequisites:
- Having taken or currently taking the artificial intelligence course
- Talking to the instructor about the knowledge in AI
Course Introduction:
This course focuses on intelligent agents from their mechanisms to their applications in different domains. The intelligence of a system is stressed throughout the course by applying different techniques from artificial intelligence and expert systems. Intelligent agents are proactive entities that are capable of residing in different platforms. A multiagent system consists of a multiple number of agents by utilizing the cooperation ability in agents. Furthermore, the development of a multiagent system is conducted based on software engineering practices.
The goal is to understand intelligent agent systems from theoretical and practical points of view.
Learning Goals:
1. Understanding IA systems from theoretical and practical points of view
2. Learning knowledge engineering
3. Practicing developing agent systems
4. Knowing the issues in multiagent systems
Textbook:
Main reference book:
- Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd Edition, Prentice Hall, 2010 (http://aima.cs.berkeley.edu/)

Other reference books:
- J. Giarratano and G. Riley, Expert Systems, Course Technology, 2005
- J.P. Bigus and J. Bigus, Constructing Intelligent Agents Using Java, Wiley, 2001
- Michael Wooldridge, An Introduction to Multiagent Systems, John Wiley & Sons 2002

Course Syllabus Number of Hours Core Capabilities Remarks
Topic Content Lecture Demonstration Assignment Others
Introduction to AI and ES
1. Something about AI
2. AI Techniques
3. Expert systems
4. CLIPS Demonstration
9 1.11.21.32.12.23.13.24.14.24.34.4
spontaneous small group discussion
Basics in Intelligent Agents
1. Events, Conditions, and Actions
2. Agents vs. Objects
3. Taxonomies of Agents
4. BDI agents
6 1.11.21.32.12.23.13.24.14.24.34.4
spontaneous small group discussion
Agent-Based Software Engineering
1. Methodology
2. Roles
3. Analysis & Design
4. Case Study
6 1.11.21.32.12.23.13.24.14.24.34.4
spontaneous small group discussion
Knowledge Representation
1. Semantic nets, frames
2. Propositional logic
3. First order predicate logic
6 1.11.21.32.12.23.13.24.14.24.34.4
spontaneous small group discussion
Inference
1. Decision tree
2. AND-OR tree
3. Production system
4. Resolution
5. Case-based reasoning
6 3 1.11.21.32.12.23.13.24.14.24.34.4
spontaneous small group discussion
Research topics
1. Cooperation, teamwork
2. Negotiation, conflict resolution
3. Ontology
4. Smart home
5. Robot soccer
6. Semantic web
9 1.11.21.32.12.23.13.24.14.24.34.4
spontaneous small group discussion

Education Goals
1.傳授學生電機工程專業領域知識,並能進一步結合理論與實務進行研究。
2.訓練學生發掘與分析解決問題的能力。
3.訓練學生良好的溝通技巧,並培養團隊合作的能力。
4.培養學生瞭解國內外學術與產業之發展與需求,並理解工程倫理及社會責任。

Core Capabilities
1.1.學習電機工程相關領域之理論基礎。
1.2.瞭解電機工程相關領域之實務技術。
1.3.訓練專業論文寫作與簡報的能力。
2.1.培養發掘與分析電機工程特定領域專題研究之能力。
2.2.培養規劃與執行電機工程特定領域專題研究之能力。
3.1.學習溝通與表達的能力。
3.2.運用個人專長,與團隊成員合作達成計畫目標。
4.1.瞭解國內外電機工程特定領域產業現況。
4.2.理解工程倫理及社會責任。
4.3.培養良好的國際觀。
4.4.培養科技英文能力。

Please respect to the intellectual property rights, do not photocopy the textbooks which assigned by professors.

Course Details:
1. Teaching Materials:Self DevelopedProvided by Textbook Authors
2. Teaching Method:Lecture SlidesBlackboard Teaching
3. Grading Method:Attendance 0%, Quiz0%, Assignment10%, Programming0%, Technical Report0%,
                       Project40%, Mid-Term Exam0%, Final Exam20%, Final Report20%, Others0%,
4. Teaching Resources:Course Web Site Downloadable Electronic Materials Lab Web Site
5. Other requirements:

Relationship between course education goals and core capabilities        
Please select:1.11.21.32.12.23.13.24.14.24.34.4
1.1 學習電機工程相關領域之理論基礎。()
Why is it related:
The topic of intelligent agents is based on the theoretical knowledge in Electrical Engineering like AI, robotics, and logic.
Achieving indicators:
To understand the basic knowledge of AI and agents.
Grading Method:
Discussion and exams
1.2 瞭解電機工程相關領域之實務技術。()
Why is it related:
Intelligent agent systems have many applications in different fields including Electrical Engineering such as robots and smart home systems.
Achieving indicators:
To build systems using tools like Clips and Jade
Grading Method:
Demonstration and discussion
1.3 訓練專業論文寫作與簡報的能力。()
Why is it related:
The term report is a survey paper that requires students to study further on the impact of agent technology.
Achieving indicators:
To write a survey paper of topics related to agents.
Grading Method:
Presentation and discussion
2.1 培養發掘與分析電機工程特定領域專題研究之能力。()
Why is it related:
By building an expert system, students need to analyze, design, and implement an intelligent system. Such training is further applied to their respected fields.
Achieving indicators:
To build prototype systems in expert systems and agent systems.
Grading Method:
Demonstration and discussion
2.2 培養規劃與執行電機工程特定領域專題研究之能力。()
Why is it related:
Building a prototype system and writing a survey paper all need a careful plan.
Achieving indicators:
To demonstrate prototype systems and do presentation on a survey paper
Grading Method:
Discussion
3.1 學習溝通與表達的能力。()
Why is it related:
Discussion and demonstration are a regular part of the class.
Achieving indicators:
To participate in discussion and demonstration
Grading Method:
Discussion
4.1 瞭解國內外電機工程特定領域產業現況。()
Why is it related:
Applications in the past and the current issues are discussed in the class.
Achieving indicators:
To have students discuss the current trends in the field and also write a survey paper.
Grading Method:
Discussion
4.4 培養科技英文能力。()
Why is it related:
Lecture notes and papers are written in English.
Achieving indicators:
To understand the reading assignments
Grading Method:
Discussion and exams