Jordan University of Science & Technology
Faculty of Computer & Information Technology
Department of Computer Science & Information Systems
Year:
2006/2007
Semester:
Second
Course Information
Course Title
Knowledge-based systems (Expert Systems)
Course Number
CIS 430
Prerequisites
M233, CIS 328
Course Website/ slides
http://www.just.edu.jo/~ayaseen
Instructor
Mr. Ashraf Yaseen
Coordinator
Mr. Ashraf Yaseen
Office Location
PH2 level 0
Office Phone
Office Hours
7201000 Ext. 23511
S.T.T: 12:15 – 1:15
or by appointment
E-mail
ayaseen@just.edu.jo
Teaching Assistant
None
M.W: 11:15 - 12:45
Course Description
Examines expert systems problems, challenges, concepts and techniques, overview of AI, knowledge
representation schemes, representing uncertainty, and CLIPS programming.
Text Book
Title
Introduction To Expert Systems
Author(s)
Peter Jackson
Publisher
Addison-Wesley
Year
1999
Edition
3ed
http://members.aol.com/JacksonPE/music1/introduc.htm
Book Website
References
Expert Systems, Principles and Programming, J.C.Giarratano, G.D.Riley, 4th
edition, 2005.
Assessment Policy
Assessment Type
Expected Due Date
Weight
First Exam
Nov 5, 2006
20%
Second Exam
Dec 3, 2006
20%
Quizzes
10%
Presentation
At the end of each chapter
TBA
Final Exam
TBA
40%
10%
1
Course Objectives
The goal of the course



Is to understand important problems, challenges, concepts and techniques from the field of KnowledgeBased Systems.
To learn the fundamental aspects of expert systems theory, design and application.
To get some hands-on experience with expert system development using the CLIPS programming
environment.
Overview: Knowledge-based expert systems, or simply expert systems, use human knowledge to solve
problems that normally would require human intelligence. These expert systems represent the expertise
knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve
problems. Books and manuals have a tremendous amount of knowledge but a human has to read and interpret
the knowledge for it to be used. Conventional computer programs perform tasks using conventional decisionmaking logic -- containing little knowledge other than the basic algorithm for solving that specific problem and
the necessary boundary conditions. This program knowledge is often embedded as part of the programming
code, so that as the knowledge changes, the program has to be changed and then rebuilt. Knowledge-based
systems collect the small fragments of human know-how into a knowledge-base which is used to reason through
a problem, using the knowledge that is appropriate. A different problem, within the domain of the knowledgebase, can be solved using the same program without reprogramming. The ability of these systems to explain the
reasoning process through back-traces and to handle levels of confidence and uncertainty provides an additional
feature that conventional programming doesn't handle.
Teaching & Learning Methods

Class lectures, and lecture notes, are designed to achieve the course objectives.

You should read the assigned chapters before class, complete assignments on time, participate in class or
the lab and do whatever it takes for you to grasp this material. Ask questions. Ask lots of questions.

You are responsible for all material covered in the class.

Please communicate any concerns or issues as soon as practical either in class, by phone or by Email.

The web page is a primary communication vehicle. Lecture notes will be available before each class. It will
contain homework assignments, study guides, and important instructions.
Course Content
Week
1
Topics
Chapter in Text
Introduction (What are Expert Systems)
1
An overview of Artificial Intelligence
2
4
Knowledge Representation
3
5
Symbolic computation
4
5
Rule-based systems
5
6
Associative Nets and Frame systems
6
7
Representing Uncertainty
9
2, 3
2
8
Knowledge Acquisition
10
9
Heuristic Classification
11
9
Constructive problem solving
14
10
Designing for explanation
16
11
Tools for building expert systems
17
12
Summary and conclusion
24
Additional Notes
Exams

The format for the exams is generally (but NOT always) as follows: MCQs,
True/False, and essay questions.
Makeup Exams


Makeup exam should not be given unless there is a valid excuse.
Arrangements to take an exam at a time different than the one scheduled
MUST be made prior to the scheduled exam time.
Drop Date

Cheating

Last day to drop the course is before the (12th) week of the first/second
semester and the drop date will be announced for the summer.
Cheating or copying from neighbor on exam, quiz, or homework is an illegal
and unethical activity.
Standard JUST policy will be applied.
All graded assignments must be your own work (your own words).
Some of the assignments (programming or homework) may be graded orally.



Attendance




Excellent attendance is expected.
JUST policy requires the faculty member to assign ZERO grade (35) if a
student misses 10% of the classes that are not excused.
Sign-in sheets will be circulated.
If you miss class, it is your responsibility to find out about any
announcements or assignments you may have missed.
Graded Exams

Instructor should return exam papers graded to students not after the week
after the exam date.
Participation

Participation in, and contribution to class discussions will affect your final
grade positively. Raise your hand if you have any question.
Making any kind of disruption and (side talks) in the class will affect you
negatively.

Finally



Make backups of all of your work.
This includes any assignment and project materials you and your group
produce.
Copy files onto 2 or 3 floppy disks and photocopy diagrams and other
materials to share with your group
3