CSE 4308/5360 - Fall 2008 - Syllabus

Course web page: http://vlm1.uta.edu/~athitsos/courses/cse4308_fall2008/
Lecture times: Tuesday and Thursday, 2:00pm - 3:20pm
Classroom: NH 110

Textbook:
S. Russell and P. Norvig, "Artificial Intelligence: A Modern Approach", second edition, Prentice Hall, 2003
Instructor:
Vassilis Athitsos

Office: NH 309
Office hours: Monday and Wednesday: 2:30-3:30pm, Tuesday and Thursday: 3:30pm-4:30pm, until 12/11/2008.
Teaching assistant:
John Staton
E-mail: FIRST-NAME DOT LAST-NAME AT mavs DOT uta DOT edu
Office: NH 247
Office hours: Monday, Tuesday, Wednesday: 4:30pm-6:00pm.


Course Description

Contents and Objectives:
 
This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.

Prerequisites:
 
All students are expected to have passed the courses Programming Languages (CSE 3302) and Theoretical Concepts (CSE 3315) or an equivalent before attending this course.  

Textbook:
 
S. Russell and P. Norvig, "Artificial Intelligence: A Modern Approach", second edition, Prentice Hall, 2003 

Course Materials:
 
Additional course materials such as lecture notes, assignments, and 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 some programming and all students will have an account on the ACS machine omega. If not otherwise stated on the assignment homework assignments can be programmed in the language of your choice but have to compile and run on omega. If partial code is provided, however, it will generally be only provided in a limited number of languages. 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/cse4308. 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.


Grading

Exams:
 
There will be three exams in this course (two midterms and a final). The first 2 exams cover the content of the indicated chapters in the book. The final exam is cumulative and will cover all materials of the course. If for any such reason you can not attend an exam, inform the instructor as early as possible.

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

STUDENTS ARE FREE TO USE ANY BOOKS AND NOTES THEY WANT DURING THE EXAM.

CSE 5360:
 
For students enrolled in the graduate section CSE 5360 the homework assignments, as well as the exam will contain additional problems which are not required for students of CSE 4308. 

Grading Policy:
 
Exams and homework assignments will contribute to the overall grade in the following way:

CSE 4308:
Written Assignments 15%
Programming Assignments 25%
ABET Assessment Outcome E (Identifying, Formulating, and Solving Engineering Problems) 10%
Midterm 1 15 %
Midterm 2 15 %
Final exam 20 %
Undergraduate students achieving a semester grade of C or better, but failing the assessment (below 60%) and documenting their circumstances will be assigned a semester grade of I (incomplete) and may re-attempt the assessment in the next semester. If the assessment is then passed, the semester grade will be changed from I to the achieved grade.

CSE 5360:
Written Assignments 20%
Programming Assignments 30%
Midterm 1 15 %
Midterm 2 15 %
Final exam 20 %



CSE 4308/5360 - Fall 2008 - Schedule

CSE 4308 / CSE 5360 - Artificial Intelligence I
Textbook: S. Russell and P. Norwig, "Artificial Intelligence: A Modern Approach",
second edition, Prentice Hall, 2003
Tentative Lecture and Assignment Schedule
Fall Semester 2008 - TuTh 2:00 - 3:20
Class Date Textbook Readings Other Readings Lecture Topics Assignments
1 08/26 1 Slides ((c)S. Russel) Course Details and Overview  
2 08/28 2 Slides ((c)S. Russel) Introduction to AI and Agents  
3 09/02 3 Slides ((c)S. Russel) Solving Problems by Search  
4 09/04 3 Some notes on implementation Search continued  
5 09/09 4   Search continued  
6 09/11 4 Slides ((c)S. Russel, Cook) Search continued  
7 09/16 4   Search continued P1 due 9/15
8 09/18 6 Slides ((c)S. Russel) Game Playing W1 due in class
9 09/23 6   Game Playing continued  
10 09/25 7 Slides ((c)S. Russel) Knowledge and Logic Reasoning  
11 09/30 8 Slides ((c)S. Russel) First Order Logic, Knowledge Engineering P2 due 09/29
12 10/02 8   Proofs W2 due in class
13 10/07     Exam 1
14 10/09 9 Slides ((c)S. Russel) Resolution - Unification  
15 10/14 11 Slides ((c)S. Russel) Planning  
16 10/16 11 Slides part 1((c)S. Rajendran),
Slides part 2((c)S. Rajendran)		 Planning continued  
17 10/21 12 Slides ((c)S. Russel) Conditional Planning and Replanning W3 due in class
18 10/23 13 Slides ((c)S. Russel) Uncertainty  
19 10/28 14.1-14.3 BN Slides ((c)S. Russel) Probabilistic Reasoning P3 due 10/27
20 10/30 14.1-14.3   Probabilistic Reasoning  
21 11/04 18.1 - 18.4 Slides ((c)S. Russel) Learning Methods  
22 11/06 18.1 - 18.4   Learning Methods  
23 11/11     Learning Methods P4 due 11/10
24 11/13 18.1 - 18.4   Review for second midterm W4 due in class
25 11/18 20   Exam 2
26 11/20 20 Slides ((c)S. Russel) Statistical Machine Learning  
27 11/25 20 Slides ((c)S. Russel) Statistical Machine Learning  
  11/27 Thanksgiving - No Class
28 12/02 20   Statistical Machine Learning P5 due 12/02, W5 due in class
29 12/04     Conclusions and Review  
30 12/09     Final Exam, 2:00pm-4:30pm.
Covers all Course Material

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