담당교수
(INSTRUCTOR)

년도
(YEAR)

학기
(SEMESTER)

교과목번호
(COURSE NUMBER)

교과목명 (COURSE NAME)

분반
(SECTION)

권혁철
(KWON,HYUK CHUL)

2016

1

CP21845

 인공지능
(ARTIFICIAL INTELLIGENCE)

059

담당교수메일 / 연락처

 hckwon@pusan.ac.kr  /  C26-407(2218)

상담가능한 시간

 

 

1.교수목표 및 강의개요 (Course Objectives & Description)

1)
교수목표
- To understand the basic concept of problem solving by searching and apply it to practical problems - To cultivate the ability to formalize real-world problems and solve them by using logical or mathematical reasoning methods - To study various learning algorithms and apply them to real-world problems – To understand current applications of AI

2)
강의개요
The course introduces students the methods of search, knowledge representation, inference and the theories of learning as computational models useful in the implementation of intelligent systems. This course will contain basic concept and some applications of uncertain reasoning. The application system using AI techniques such as robotics, expert systems, and natural language processing will also be introduced. 
* 장애학생의 경우 장애학습지원센터와 강의 및 과제에 대한 사전 협의가 가능합니다.

2.
주교재 (Required TextBook)
Artificial Intelligence: A Modern Approach, 3rd ed. Stuart Russell and Peter Norvig, Prentice Hall, 2009

3.
평가방법 (Requirements & Grading)
- Mid.Exam:40% - Final.Exam:40% - Assignment:20%
* 장애학생의 경우 시험시간의 연장이 가능하며, 대필이나 컴퓨터를 활용하여 시험에 응할 수 있습니다.

4.
주별 강의계획 (Schedule)

주 별

강의 및 실험실기내용

과제 및 기타 참고사항

1

 [표절 등 학술적 부정행위 예방교육실시] Introduction, Solving Problems by Searching

2

 [표절 등 학술적 부정행위 예방교육실시] Informed Search and Exploration

Homework #1: Search Application and Implementation

3

 Constraint Satisfaction Problems

4

 Logical Agents

5

 Reasoning & Knowledge Representation

6

 Uncertainty

Homework #2: Exercise

7

 Uncertainty (continued)

8

 Bayesian Networks, Midterm Examination

Homework #3: Exercise

9

 Inference in Bayesian Networks

10

 Bayesian and Prior Knowledge

11

 C4.5 and Rule Learning

Homework #4: Exercise

12

 Learning from Observations

13

 Learning from Observations (continued)

Homework #5: Implementation of Learning Application

14

 Statistical Learning Methods

15

 Final Examination

16

 



5.
참고문헌 (References)
Related videos(EBS documentary etc.)