Course Description:
Artificial Intelligence (AI) is still a research discipline in attempting to understand the mechanisms underlying intelligent behavior and to build "intelligent systems" from variety of mechanical and electronic devices. This course is to offer an introduction to artificial intelligence covering from mechanism, models, algorithm to some typical AI applications as well. The course AI covers the following interesting topics: a brief history of AI, research and philosophical questions faced by AI practitioners, representing and solving AI problems in a state space search formalism, heuristics, connectionism, and specific AI problems such as vision, natural language and robotics.

Course Objectives:
To develop the student's understanding of the issues involved in trying to define and simulate intelligence.
To familiarize the student with specific, well known Artificial Intelligence methods, algorithms and results.
To provide the student additional experience in the analysis and evaluation of complicated systems.
To provide the student with paper and proposal writing experience.

Prerequisites: Advanced Programming, Mathematical Logic

Students will be graded on their understanding of the course as reflected in their performance on the homework, class participation, examinations, and projects as follows (approximately):

Homework 20% + Projects 40% + Final Exams 40%

Liqing Zhang, Prof.
Office: Room 3-435, SEIEE Building
Tel: 34204423

Bo Yuan, Ph.D., Prof.
Office: Room 3-401, SEIEE Building
Phone: 131-6211-5543

Textbook and References:
Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, Englewood Cliffs, New Jersey, 2003.
[1] George Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Addison-Wesley, 2008
[2] Nils Nilsson, "Artificial Intelligence", Morgan Kaufman, 1998