Course Title : Artificial Intelligence

Code 91160
Course Year 3rd year
Term 1st term
Class day & Period
Location
Credits 2
Restriction No Restriction
Lecture Form(s) Lecture
Language
Instructor

Course Description

This lecture introduces basic technologies of artificial intelligence. Topics will be selected from search, knowledge representation, and learning.

Grading

By reports and a final examination.

Course Goals

Learning the concept of artificial intelligence and the basic models and algorithms of search, knowledge representation, and learning.

Course Topics

Theme Class number of times Description
Introduction 1 Introducing the history of artificial intelligence researches.
Search 3-4 Introducing breadth-first search, depth-first search, heuristic search, AND/OR-graph search, adversarial search, constraint satisfaction, etc. It comes with exercise. Applications of search techniques such as computer chess, Sudoku, are also introduced.
Knowledge representation 4-5 Introducing semantic network, production system, Bayesian network, predicate logic, etc. It comes with exercise. Applications of knowledge representation techniques such as semantic web are also introduced.
Learning 5-6 Introducing decision tree learning, perceptron, SVM, genetic algorithm, reinforcement learning, etc. It comes with exercise. Applications of machine learning techniques such as data mining are also introduced.

Textbook

Materials will be distributed.

Textbook(supplemental)

S. Russell and P. Norvig, Artificial Intelligence A Modern Approach, Prentice Hall, 1998.
M. Ginsberg, Essentials of Artificial Intelligence, Morgan Kaufmann, 1993.
P.H. Winston, Artificial Intelligence, Addison-Wesley, 1992.

Prerequisite(s)

Web Sites

Additional Information