CPSC 625-600 Artificial Intelligence:
Fall 2005


NEWS: 12/15/05, 12:06PM (Thu)
Read-Only Bulletin Board.: 8/31/04, 12:02PM (Tue)

Page last modified: 11/22/05, 10:01AM Tuesday.

General Information Resources Weekly Schedule Credits Lecture Notes Example Code Read-Only Board

I. General Information


Dr. Yoonsuck Choe
Email: choe(a)tamu.edu
Office: HRBB 322B
Phone: 845-5466
Office hours: T/TR 10:00am-11:00am. Other times: by appointment only.


Yingwei Yu
Email: yingweiy(a)cs.tamu.edu
Office: HRBB 322A
Phone: 845-5481
Office hours: T 1:30-3:00pm, F 2:00-3:30pm in HRBB 322A.


CPSC 311


T/TR 11:10am-12:25pm, ZACH 105B


To understand the problems in AI and to learn how to solve them:
  1. traditional methods in AI (search, pattern matching, logical inference, theorem proving, etc.).
  2. modern approaches in AI (learning, probabilistic approaches, etc.).


Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (AIMA, hereafter), 2nd Edition, Prentice Hall, New Jersey, 2003.
ISBN 0-13-790395-2
Book Homepage
* The first edition may be okay if that's what you have.

Computer Accounts and Usage:

  1. Computer accounts: if you do not have a unix account, ask for one on the CS web page. We will be using the CMU Common Lisp as our main language. Example code will only be made available in Lisp, and in general other languages will not be permitted.
  2. CMU Common Lisp:

Topics to be covered:

See the Weekly Schedule section for more details.
  1. Introduction : 1 week
  2. LISP : 1 week
  3. Search : 1.5 weeks
  4. Game playing, alpha-beta pruning: 0.75 week
  5. Propositional Logic, first-order logic, theorem proving: 3.5 weeks
  6. Uncertainty, probabilistic approaches: 1.5 weeks
  7. Learning: 2 weeks
  8. Special topics : 1 week


  1. Exams: 45% (midterm: 20%, final: 25%)
  2. Homeworks: 15% (about 3, 5% each)
  3. Programming Assignments: 36% (about 3, 12% each)
  4. Paper commentary: 4% (1 page, single-spaced)
Grading will be on the absolute scale. The cutoff for an `A' will be 90% of total score, 80% for a `B', 70% for a `C', 60% for a `D', and below 60% for an 'F'.

Academic Policy:

The TAMU student rules (http://student-rules.tamu.edu/), Part I Rule 20 will be strictly enforced. Local Course Policy:

Students with Disabilities:

Americans With Disabilities Act (ADA) Policy Statement: The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact the Department of Student Life: Services for Students with Disabilities in Room 126 of the Koldus Building, or call 845-1637.

II. Resources

  1. LISP quick reference
  2. CMU Common Lisp (This one will be used in the class.)
  3. GCL manual (very in-depth and technical).
  4. GNU Common Lisp
  5. Lisp resources
  6. My general resources page
  7. 625/689 Reading List
  8. An interesting popular view of AI

III. Weekly Schedule and Class Notes

Notices and Dues
1 8/30 Introduction Chapter 1
1.1 and 1.2
  First day of class slide01.pdf
1 9/1 Introduction Chapter 26
26.1 and 26.2
  Unix basics (DIY); Last day to drop a course is 9/2 slide01.pdf
2 9/6 Lisp Lisp quick ref     slide02.pdf
2 9/8 Lisp (Symbolic Differentiation)   Prog. Asmt. #1 announced   slide02.pdf
3 9/13 Uninformed Search (BFS,DFS,DLS,IDS) Chapter 3.1-3.5 (3.6,3.7 optional)     slide03.pdf
3 9/15 IDA*,Heuristic Search,
Simulated Annealing, etc.
Chapter 4   slide03.pdf
4 9/20 Informed Search (BestFS,Greedy,A*) Chapter 4.1-4.3 (4.4 optional)(old 4.1-4.3)     slide03.pdf
4 9/22 Game playing
Min-Max, Alpha-Beta
Chapter 5 (optional) and 6.1-6.8 (old 5) Prog. Asmt. #2 announced Prog. Asmt. #1 due changed to Monday 9/26 (midnight) slide03.pdf
5 9/27 Game playing wrap up; Propositional Logic Chapter 7.1, 7.3, 7.5, 7.6 (old 6) HW#1 Announced   slide03.pdf
5 9/29 Theorem proving Chapter 9 (old 10)   slide04.pdf
6 10/4 First-order logic Chapter 8 (old 7) HW#2 announced HW#1 due slide04.pdf
6 10/6 Inference
for FOL
Chapter 9     slide04.pdf
7 10/11 Theorem proving
for FOL
Chapter 9 (old 10)   HW#2 due; Midterm review slide04.pdf
7 10/13 Midterm Exam   In class exam.  
8 10/18 Uncertainty Chapter 13 (old 14)   10/17: Midsemester grades due. slide05.pdf
8 10/20 Uncertainty (continuted) Chapter 13 (old 14)     slide05.pdf
9 10/25 Probabilistic
Chapter 14 (old 15)   Program #2 due 10/26 slide05.pdf
9 10/27 Learning Chapter 18     slide06.pdf
10 11/1     11/5 (Q-drop) slide06.pdf
10 11/3   Prog. Asmt. #3 announced;
Homework #3 announced
11 11/8 Learning (Nnets) Chapter 20 (old 19)     slide06.pdf
11 11/10 Guest Lecture Yingwei Yu: Topic TBA      
12 11/15 No class Society for Neuroscience meeting: Make-up session:11/7 5:45pm HRBB 302      
12 11/17 Autonomous semantics Special topics Paper Commentary Asmt. announced Course evaluation;
Homework #3 due (in class);
Mini project proposal due (in class)
13 11/22 No class Make up to be announced (out-of-class final exam review session)      
13 11/24 Thanksgiving     No class  
14 11/29 Guest Lecture Heejin Lim will give a guest lecture on delay compensation in the nervous system      
14 12/1 Natural language processing       slide08.pdf
15 12/6 Advanced topics Analogy   Last day of class.
Program #3 due (midnight)
 12/9Final Exam  3:00--5:00pm, ZACH 105B
Paper commentary due (in class)

IV. Credits

Many ideas and example codes were borrowed from Gordon Novak's AI Course and Risto Miikkulainen's AI Course at the University of Texas at Austin (Course number CS381K).

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