CSE 5361 - Spring 2008 - Syllabus

Course Description

Contents and Objectives:
 
This course describes the AI techniques necessary for an agent to act intelligently in the ``real'' world. Techniques include uncertainty reasoning, learning, natural language processing, vision and speech processing. Basic AI techniques (such as search, knowledge representation and planning) will be reviewed. Emphasis will be on implementation and experimentation with the goal of building robust intelligent agents.

Students in this course will be introduced to modern artificial intelligence techniques which enable computer systems to interact with the world and the computer user. This permits efficient decision making by computer programs and is therefore an essential component of future, interactive computer software. Students successfully completing this course will be able to apply a variety of techniques for the design of intelligent agents to address complex problems.

Prerequisites:
 
All students are expected to have passed Artificial Intelligence I (CSE 5361).  

Textbooks:
 
S. Russell and P. Norwig, ``Artificial Intelligence: A Modern Approach'', Second edition, Prentice Hall, 2003 

Course Materials:
 
Additional course materials such as assignments and example solutions will be available electronically on the course web page. Changes and corrections, if any, will also be announced by e-mail. 

Computer Access:
 
This course will require programming and all students will have an account on the ACS machines gamma and omega. If not otherwise stated homework assignments will be programmed in C++, Java, or Matlab. Additional details will be announced in class.

E-mail and WWW page:
 
There is a course web page at http://vlm1.uta.edu/~athitsos/courses/cse5361_spring2008. All changes and supplementary course materials will be available from this site. In addition, necessary changes or important announcements will also be distributed by e-mail.

Instructor:
 
Vassilis Athitsos

Office: NH 309
Office hours: Tuesday and Thursday, 10:00am-11:00am.

Teaching assistant:
 
Rosina Khan
E-mail: surovi99 at-sign yahoo dot com
Office: NH 235
Office hours: Tuesday and Thursday, 4:00pm-5:30pm.


Grading

Grading Policy:
 
Students can select one of two grading options:

Option 1 (default option):
Programming assignments 65%
Class project 25%
Class participation 10%

Option 2 (by arrangement with instructor):
Class project 75%
Written assignments 15%
Class participation 10%

Any request for re-grading (for an assignment or exam) must be made within two weeks of receipt of that grade.


Schedule

CSE 5361 - Artificial Intelligence II
Spring Semester 2008 - TuTh 2:00 - 3:20
Textbook: S. Russell and P. Norwig, "Artificial Intelligence: A Modern Approach",
second edition, Prentice Hall, 2003
Tentative Lecture and Assignment Schedule
Class Date Readings Lecture Topics Additional links
1 01/15   Course Details and Overview Turing paper
2 01/17 RN:2 Intelligent Agents Slides ((c)S. Russel)
3 01/22 RN:11-12 Agents using Search and Planning Slides ((c)S. Russel)
4 01/24 RN:11-12 Planning and Uncertainty Slides part 1, part 2 ((c)S. Rajendran)
5 01/29 RN:11-12 Planning and Uncertainty Slides ((c)S. Russel)
6 01/31 RN:24 Computer Vision Slides ((c)S. Russel)
7 02/05 RN:24 Computer Vision Example image operations
8 02/07 RN:24 Computer Vision  
9 02/12 RN:13 Uncertainty Slides ((c)S. Russel)
10 02/14 RN:14 Belief Networks Slides ((c)S. Russel), More slides ((c)S. Russel)
11 02/19 RN:15 Temporal Probability Models Slides ((c)S. Russel), More slides ((c)S. Russel)
12 02/21 RN:15 Hidden Markov Models  
13 02/26 RN:15 Hidden Markov Models  
14 02/28 RN:18-19 Machine Learning Slides ((c)S. Russel)
15 03/04 RN:18-19 Machine Learning  
16 03/06 RN:20 Statistical Learning Slides ((c)S. Russel)
17 03/11 RN:20 AdaBoost  
18 03/13 RN:20 Neural Networks Slides ((c)S. Russel)
  03/18   Spring Vacation- No Class  
  03/20   Spring Vacation- No Class  
19 03/25 RN:20 Neural Networks  
20 03/27 RN: 16 Utility Functions Slides ((c)S. Russel)
21 04/01 RN:17 Markov Decision Processes Slides ((c)S. Russel)
22 04/03 RN:17 Partially Observable MDPs  
23 04/08   Current Issues  
24 04/10   Current Issues  
25 04/15 RN:21 Reinforcement Learning  
26 04/17 RN:21 Reinforcement Learning  
27 04/22   Genetic Algorithms  
28 04/24 RN:22 Natural Language Slides ((c)S. Russel)
29 04/29   Speech  
30 05/01   Project Presentations  

This schedule is tentative and subject to change. If changes are necessary they will be announced in class and posted in the schedule on the course page.


Ethics, Professionalism, and Academic Integrity

A. Cheating

Students are expected to know university policies. If students are suspected of cheating, the matter must go through university channels outside of the CSE Department.

B. Academic Integrity Policy

It is the policy of the University of Texas at Arlington to uphold and support standards of personal honesty and integrity for all students consistent with the goals of a community of scholars and students seeking knowledge and truth. Furthermore, it is the policy of the University to enforce these standards through fair and objective procedures governing instances of alleged dishonesty, cheating, and other academic/non-academic misconduct.

Students can assume responsibility in two ways. First, if they choose to take the risk associated with scholastic dishonesty and any other violation of the Code of Student Conduct and Discipline, they must assume responsibility for their behaviors and accept the consequences. In an academic community, the standards for integrity are high. Second, if they are aware of scholastic dishonesty and any other conduct violations on the part of others, they have the responsibility to report it to the professor or assistant dean of students/director of student judicial affairs. The decision to do so is another moral dilemna to be faced as students define who they are. Students who violate University rules on scholastic dishonesty are subject to disciplinary penalties, including the possibility of failure in the course and dismissal from the University. Since dishonesty harms the individual, all students, and the integrity of the University, policies on scholastic dishonesty will be strictly enforced.

C. Statement on Ethics, Professionalism, and Conduct of Engineering Students

The statement can be