Course Description

Introduction to principles and programming techniques of artificial intelligence, strategies for searching, representation of knowledge and automatic deduction, learning, adaptive systems, and applications of artificial intelligence.

Pre-requisites

305214: Fundamental of Data Structures and Algorithms

Course Outline

This course covers the following topics (tentative):

Introduction
Problem Solving by Search
- Uninformed Search
- Informed Search
- Constraint Satisfaction
Machine Learning
- Decision Trees
- Bayesian
- Rule-based
- Nearest Neighbors
Knowledge Representations
- DAML
- Web Ontology
- RDF

Assessment

Assessment Item	Worth
Assignments	35%
Midterm Exam	25%
Final Exam	40%

Resources

Required readings come directly from the course lecture notes, and the recommended textbook for this course is:

Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. 2nd edition. Upper Saddle River, NJ: Prentice Hall, 2003. ISBN: 0137903952.

Staff

Woralak Kongdenfha