Old Web Page for
CPSC 625-600 Artificial Intelligence:
Fall 2002


  1. Final letter grades are available now. No more seminar credits are accepted.
  2. NEW!: Final exam guideline in the undergrad board.
  3. Homework 1 grades are available.
  4. Final exam material: 30% First-order logic, 30% Reasoning in Uncertain Domain, 40% Learning.
  5. Final exam review: Friday 12/6/02.
  6. Homework solution is now available.
  7. Project 2 scores are out: grades.
  8. If you think some of the homework answers you turned in today were insufficient or erroneous, you may revise it and turn it in by Monday 11/18 in class (* notice the further extension! *). Also see Gordon Novak's predicalculus story problems.
  9. I've put up some Q&A's in the board.
  10. Clarification about homework: a and b are constants, not variables. The written homework is due by 11/13 Wednesday in class.
  11. Final exam: 12/16/02 10:30am-12:30pm.
Old Stuff
  1. I'll be on another trip (the last one this semester ; 11/7 evening--11/10). This time, there will be no class. Instead, you should attend this on-line seminar by James McClelland at CMU on Semantic Cognition (you need Flash pl ayer; the talks consists of automatically advancing slides + audio). You may sub mit a report for seminar extra credit.
  2. Term project information was added below. Check it out.
  3. I'll be out of town again (10/31-11/5). Dr. Xu will do a guest lecture on Planning (11/1), and Dr. Gutierrez will do a (virtual) guest lecture on Principal Components Analysis (11/4). You may write a report for either lecture to earn 1 seminar extra credit.
  4. You may turn in the term project proposal by Monday, 10/28.
  5. GCL path was changed: /pub/www_faculty/daugher/gcl/gcl
  6. Project extension: new due is 10/28 in class.
    Those of you who submit by 10/21 in class will get 10% extra credit.
  7. Important: read the bulletin board to keep up to date on the programming issues.
  8. For those without a project partner: please send me email immediately (choe(a)tamu.edu).
  9. Midterm on Friday 10/18 (up to and including propositional logic)! (Project due is 10/21 in class).
  10. Project #1: dfs.lsp, a simple depth first search skeleton code.
  11. Project #1: required user interface.
  12. Past exam (midterm): see 02Spring lecture slide 20 for solution.
  13. Reading List Updated!: section 1, section 2 (netlibrary),
    and section 5 (skeleton tools). Also look for new links added for books (and papers).
  14. Readling List: enter 625 showme
  15. Research Interests: find a partner for the term project.
  16. Prog Assignment #1: grades
  17. Project #1 Skeleton: eight-util.lsp and example run.
  18. alpha-beta pruning exercise: ab.pdf
  19. Announcement: Extra Credit: details below
  20. Send email to Hao Xiong: hxiong(a)cs.tamu.edu
[Read-Only Bulletin Board]
*. All email submissions should be in PLAIN ASCII TEXT.
*. Do not send word docs.

Keep an eye on this news box for the latest.


Goals | Textbook | Admin | Topics | Grading | Acad. Policy | Resources | Calendar | Weekly Sched | Lecture Notes | Assignments


Dr. Yoonsuck Choe
Email: choe(a)tamu.edu
Office: HRBB 322B
Phone: 845-5466
Office hours: MWF 1:30-2:30PM, and other times by appointment.


Dwi Widyantoro
Email: dhw7942(a)cs.tamu.edu
Office: HRBB 326
Phone: 845-8865
Office hours: T/W/TH 2:30pm-3:30pm, HRBB 326.

Hao Xiong
Email: hxiong(a)cs.tamu.edu
Office: HRBB 336
Phone: ???-????
Office hours: MWF 2:00pm-3:00pm, HRBB 336


CPSC 311


MWF 12:40-1:30p HRBB 104


To understand the problems in AI and learn the diverse approaches in solving the problems:
  1. traditional AI techniques (search, pattern matching, logic, theorem proving, etc.) to tangible problems.
  2. modern approaches in AI (learning, genetic algorithms, etc.).
  3. inspirations from processes in the brain.
* Note that this is an introductory course and there may be a lot of overlap with the undergrad CPSC 420. Those of you who have already taken an equivalent of CPSC 420 may not gain much in this class.


Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, New Jersey, 1995.
ISBN 0-13-103805-2
Book Homepage

Administrative Trivia:

  1. Computer accounts: if you do not have a unix account, ask for one on the CS web page. We will be using the GNU Common Lisp as our main language. You can choose your own language to use for the assignments, but you have to first get permission from the instructor.
  2. GNU Common Lisp:
    Installed in /usr/local/bin/gcl on all CS unix machines (robert, dogbert, etc.).

Topics to be covered:

See the Calendar section below for reading and other assignments for each week.
  1. Introduction : 1 week
  2. LISP : 1 week
  3. Search : 3 weeks
  4. Game Playing : 1 week
  5. Propositional Logic, Predicate Calculus : 4 weeks
  6. Learning : 2 weeks
  7. Special Topics : 2 weeks


  1. Exam: midterm (20%), final(20%)
  2. Homeworks: 6% (about 2 paper-pencil homeworks)
  3. Programming Assignments: 24% (about 2 mini-projects)
  4. Project: 30% (1 major project)
Grading will be on the absolute scale. The cutoff for an `A' will be at most 90% of total score, 80% for a `B', 70% for a `C', and 60% for a `D'. However, these cutoffs might be lowered at the end of the semester to accomodate the actual distribution of grades.

Academic Policy:

All incidents of academic dishonesty will be dealt with according to the university policy. No exceptions.


  1. Grodon Novak's AI Course and Risto Miikkulainen's AI Course at the University of Texas at Austin (CS381K).
    * many ideas in the current lectures were borrowed from these courses
  2. LISP online manual from the book Common Lisp, the Language (NEW: 2/3/02)
  3. LISP quick reference
  4. GCL manual (very in-depth and technical).
  5. GNU Common Lisp
  6. Lisp resources
  7. CPSC 320 : Dr. Daugherty's course page, by Lydia Tapia (your TA). this course)
  8. My general resources page
Interesting Stuff:
  1. Little wings, big flap: insect flight.


Fall Semester 2002 *

August 28-30 Wednesday-Friday. Registration.
August 30 Friday. Last day to register for fall semester classes and pay fees.
September 2 Monday. First day of fall semester classes.
September 5 Thursday. Last day for dropping courses with no record.
September 6 Friday. Last day for adding courses for the fall semester.
September 13 Friday. Last day to apply for all degrees to be awarded in December.
October 3 Thursday. Academic Convocation. Classes will be held.
October 21 Monday. Mid-semester grades due in Registrar’s Office, noon.
November 8 Friday. Last day for all students to drop courses with no penalty (Q-Drop).
Last day to change Kinesiology 198/199 to S/U grade on BONFIRE.
Last day to officially withdraw from the University.
November 11 -
December 12
Monday-Thursday. Pre-registration for 2003 spring semester.
November 28-29 Thursday-Friday. Thanksgiving. Faculty and staff holiday.
December 9 Monday. Redefined day, students attend their Friday classes.
Dead day, classes meet but no major exams.
December 10 Tuesday. Last day of fall semester classes.
Redefined day, students attend their Thursday classes.
Dead day, classes meet but no major exams.
December 11-12 Wednesday-Thursday. Reading days, no classes. 
December 13, 16-18 Friday, Monday-Wednesday. Fall semester final examinations for all students.
December 20** Friday. Final grades for all students due in Registrar’s Office, noon.
Last day for undergraduate degree candidates for December to apply for $1000 Tuition Rebate, 5:00pm.
December 20-21 Friday-Saturday. Commencement and Commissioning.
December 23-31 Monday-Tuesday. Faculty and staff holiday.

*All dates and times are subject to change.
**To have sufficient time to process grades and send data to deans and students, all final grades need to be received by noon on this date.
Approved 2/12/2002 (OAR)

Weekly Schedule and Class Notes

Lecture notes (in PDF format) (all notes will be put in this directory)
  1. Week 1:
    Chapter 1 up till and including 1.2 :required
    Section 1.3-end of chapter 1: optional
    Chapter 26 pp. 817-824 (up till, but not including mathematical objections): required
    Sections 26.4-end of chapter 26: required.
  2. Week 2 : Lisp quick reference : required
    Quick reference
    * I recommend that you try out the examples in the reference guide using gcl on the departmental unix machines.

    Lisp drill (symbolic differentiation): handout will be available in class during week 2.

    Here's a small example that will help you get started:
    Create a file "test.lsp" containing this line:
    	(defun mysqr (x) (* x x))
    and save it. Then, run gcl and load it like below, and then
    run the newly defined function mysqr.
    >(load "test.lsp")
    Loading test.lsp
    Finished loading test.lsp
    >(mysqr 100)
    >(mysqr 5)
  3. Week 3 :
    Chapter 3: sections 3.3-3.7 (required)
    Other sections: optional
    Chapter 4: upto, and including 4.2 (required).
  4. Week 4 :
    Chapter 4: 4.3--4.5 (required)
    Chapter 5: 5.1--5.3 (required)
    Chapter 5: 5.4--5.8 (required)
  5. Week 5 :
    Chapter 6: 6.3-6.4 (required)
    See Chapter 9 for theorem proving (optional; this lectures will cover these techniques applied to propositional logic) Project 1: 8-puzzle with various search methods
  6. Week 6 :
    Chapter 7: 7.1--7.3 (required)
  7. Week 7 :
    Chapter 9: required Chapter 10 sections 10.1, 10.2, and 10.4: required
  8. Week 8 :
    Chapter 10: required
  9. Week 9 :
    Chapter 14: required
  10. Week 10 :
    Chapter 15: required
  11. Week 11 :
    Chapter 19: required
  12. Week 12 :
    Chapter 19: required
  13. Week 13 :
    Chapter 18 (18.1-18.5): required
  14. Week 14 :
    Final exam review.
* When reading the chapters, you do not have to memorize everything. A separate list of terms you need to know will be handed out prior to each exam. *


  1. Assignment #1: see slide03.pdf, page 13.
  2. Programming Assignment #1: slide04-grad.pdf page 16 (this was actually project 1)
  3. Project: due on 10/21, in calss. (This is project 2).
  4. Term project information

Extra Credit for Attending Talks

  1. 1 point per each seminar or talk you attend, up to 5 points out of 100 scaled total.
  2. Seminar topic should be related to AI in general.
  3. Submit two paragraphs: first paragraph summarizing the seminar, and the second paragraph including your thoughts (why was it interesting? any new ideas you have? etc.)
  4. Either type and print or write up and submit to the instructor in the class immediately following the seminar.
  5. Seminars:

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