CS 724: Survey of AI

Class Number: #8263

TR 9:30-10:45
IACC, Rm. #106

Office hours: see Spring 2007 Schedule, or by appt.
CS724 Grader: shyam.narayanankutty@ndsu.edu

Dr. Brian M. Slator

Computer Science Department
North Dakota State University
Office: IACC #258-A24
Phone: 701-231-6124
Fax: 701-231-8255

Announcements, etc

  • NOTE: It seems that the 4th edition of the Luger textbook has one less chapter than the 5th edition, which is the current version being sold in the Varsity Mart.

    The 5th edition has a Chapter 5: Stochastic Methods, that is not included in the 4th edition. It is important to note that the chapter numbers on this web page are ONLY from the 5th edition.

  • Lisp Assignment 3 (100 points) Due Tuesday, April 3 at midnight via email to the TA.

  • Exam #2 will be on Thursday, April 12, and will cover
    • 1. AI: Early History and Applications
    • 2. The Predicate Calculus
    • 4. Heuristic Search
    • 16. Introduction to Lisp

  • The rest of the semester we will be covering
    • 7. Knowledge Representation
    • 8. Strong Method Problem Solving
    • 10. Machine Learning: Symbol-Based
    • 11. Machine Learning: Connectionist
    • 14. Understanding Natural Language
    • (and possibly 12. Machine Learning: Social and Emergent).

  • If it helps, you can use the theorem-prover-debug.txt for the assignment.

  • No Class: Thursday, March 8 (right before Spring Break)

  • Dr. Juell's State Space Search

  • Testing:

  • Dr. Juell's Microworld Page


  • Lisp Assignment 2 (50 points) Due Tuesday, March 6, at midnight via email to the TA. Using the Theorem Prover v.1

  • Dr. Juell's Introduction to Lisp page and FOPC - First Order Predicate Calculus.

  • The SHRDLU Manual is still online. It must be 35 years now.

  • Lisp Assignment 1 (25 points) Due Tuesday, Feb. 20 at midnight via email to the TA.

  • No Class: Thursday, Feb. 8th (NSF Panel, Washington, DC)

  • Exam #1: Tuesday, Feb. 6, 9:30-10:45 (during class time)
    The exam covers these articles:
    1. Computing Machinery and Intelligence, Alan Turing (20 questions)
    2. Basic Questions with John McCarthy (12 questions)
    3. ELIZA, Joseph Weizenbaum (12 questions),
    4. Dialogs with colorful personalities of early AI, by Guzeldere and Franchi (6 questions)
    On Blackboard, do not come to class
    You will have 75 minutes to complete the exam. Open book, open notes, use the internet, whatever. Just do your own work without collaborating with others -- that is the only hard rule.
    The exam will be available online under Course Documents, you can take the exam from your home, or in an NDSU cluster - whatever is most convenient to you.

  • A very brief discussion of NLP

  • For the next assignments you will need to learn LISP, to do this

To begin semester, we will be reading these classic articles


Semester Schedule

A preliminary schedule based on earlier class offererings

Course Overview

CS724 Surveys major areas of AI including theorem proving, heuristic search, problem-solving, computer analysis of scenes, robotics, natural language understanding, and knowledge-based systems. Prereq. CS 372 or Graduate standing.


Ability to deal with formal symbolic notations such as FOPC and mathematics. Skill in programming and reading programs in more than one programming language. Background in data structures and formal notations for describing programs, such as BNF grammars.


The student will: develop an understanding of the philosophy of AI and of several AI techniques, will be able to use the techniques and could evaluate the appropriateness of using the techniques for a real problem.


The student will: be able to solve problems using AI techniques within the overall AI philosophy, will be able to develop programs in LISP, or PROLOG and use other AI programming notations, will be able to present a case, in English, for using various AI techniques.


Readings in addition to the book will be required. The material will be on reserve in the library under CS724. Occasionally notices will be posted to the class home page. You are responsible for checking this information twice a week.

Problem statements, old tests and notes will be available.

General Comments

  • You are expected to be here. Come to class -- attendance will be taken semi-regularly. If you miss class, come and speak to me. This WILL affect your grade.
  • Participate, cooperate, and help others.
  • You can expect a substantial amount of outside class effort for this course.
  • This document will change over the course of the semester.
    You should check here at least once a week.
  • Periodically you might be asked to take a survey or some other in-class activity. These will not be graded, but they will be a form of taking attendance.

Required Reading:

The book for the course is: Artificial Intelligence: Structrues and Strategies for Complex Problem Solving, Fourth edition, Addison-Wesley by George Luger

The book's LISP and PROLOG programs, along with additional code and other support mattrials, are avaible at: http://www.ndsu.nodak.edu/instruct/juell/cs724s98/books/luger98

A optional book that can help with the Lisp and Prolog is:
Mueller, Robert A. and Rex L. Page, Symbolic Computing with LISP and PROLOG, John Wiley and Sons, New York, 1988. ISBN: 0-471-60771-1

Relevant Links



Grades will be assigned according to the customary system:
  • A 100%-90%;
  • B 89%-80%;
  • C 79%-70%;
  • D 69%-60%;
  • F 59% or less
Assignments and exams will be scored as follows:

Policy on Late Assignments

There is no happy way to assign lateness demerits. For the purposes of this class, it is never too late to turn in work (until grades are turned in at the end of the semester)

However, the later an assignment is produced, the less it is worth.

Therefore, the policy will be this: late assignments will lose a letter grade immediately, and then another letter grade after two weeks.

Special Needs
NDSU Academic Affairs New Course Syllabi Requirement

Any student with disabilities or other special needs, who needs special accomodations in this course, is invited to share these concerns or requests with the instructor as soon as possible.

Academic Dishonesty or Misconduct
NDSU Academic Affairs New Course Syllabi Requirement

Work in this course must adhere to the Code of Academic Responsibility and Conduct as cited in "Rights & Responsibilities of Community: A Code of Student Conduct" (1993) pp. 29-30. "The academic community is operated on that basis of honesty, integrity, and fair play. Occasionally, this trust is violated when cheating occurs, either inadvertently or deliberately .....Faculty members may fail the student for the particular assignment, test, or course involved, or they may recommend that the student drop the course in question, or these penalties may be varied with the gravity of the offense and the circumstances of the particular case."

Academic dishonesty can be divided into four categories and defined as follows:

  • Cheating: Intentionally using or attemping to use unauthorized materials, information or study aids in any academic exercise.
  • Fabrication: Intentional and unauthorized falsification or invention of any information or citation in an academic exercise.
  • Facilitating academic dishonesty: Intentionally or knowingly helping or attempting to help another to commit an act of academic dishonesty.
  • Plagiarism: Intentionally or knowingly representing the words or ideas of another as one's own in any academic exercise.

Would you like to know the Current Time?
Send comments to: slator@cs.ndsu.edu