MMIS 670 Artificial
Intelligence and Expert Systems (3 credits)
Summer 2004 (June 21 - September 10, 2004)
/Online
Instructor
Dr. James Cannady
cannady@nova.edu
(954) 262-2085
Course Description
This course will include an introduction to artificial intelligence as well as
historical and current trends and characterization of knowledge-based systems.
Search, logic and deduction, knowledge representation, production systems, and
expert systems will be examined. Additional areas include architecture of
expert systems and criteria for selecting expert system shells, such as
end-user interface, developer interface, system interface, inference engine,
knowledge base, and data interface.
Course Materials
Required Textbook: Russell & Norvig.
Artificial Intelligence: A Modern Approach (2nd Edition). 2002.
Exit Competencies
- Obtain an overview of artificial intelligence (AI) principles and
approaches.
- Develop a basic understanding of the building blocks of AI as
presented in terms of intelligent agents: Search, Knowledge
representation, inference, logic, learning.
- Obtain a brief overview of AI applications: Expert Systems and
Planners.
- Enable the student to follow AI literature with the ability to go
on to independent work in the field.
Course Outline
The course material has been divided into five modules. The modules are
designed to cover each of the major areas of Artificial Intelligence by including
readings from the text, problems from the text, practical exercises,
supplemental readings, and an online class discussion.
|
Date |
Assignment |
Deliverable |
|
06/21/-07/04/04 |
Module 1: Introduction to Artificial Intelligence |
Module 1 (due 07/04/04) |
|
07/05-18/04 |
Module 2: Searching |
Module 2 (due 07/18/04) |
|
07/11/04 |
Project Proposal |
Project Proposal (due
07/11/04) |
|
07/19/-08/01/04 |
Module 3: Machine Learning |
Module 3 (due
08/01/04) |
|
08/02-15/04 |
Module 4: Knowledge-based Systems |
Module 4 (due 08/15/04) |
|
08/16/-08/29/04 |
Module 5: Reasoning with Uncertainty |
Module 5 (due 08/29/04) |
|
08/30-09/10/04 |
Final Exam |
Final Exam (due
09/10/04) |
|
09/10/04 |
Course Project |
Project (due 09/10/04) |
Module 1:
Introduction to Artificial Intelligence
|
Assignment |
Description |
Points |
|
Text |
Chapter 1 |
- |
|
Text Problems |
1, 3, 7, 9 |
3 |
|
Article Summary |
Write a summary of Alan Turing's AI paper based on the established guidelines. |
4 |
|
Practical Exercise |
None |
3 |
|
Online Class Discussion |
06/28/04 9:00-10:00 pm (ET) -details will be provided via WebCT email |
- |
Module 2: Searching
|
Assignment |
Description |
Points |
|
Text |
Chapter 3 & 4 |
- |
|
Text Problems |
Chapter 3: 1, 2 / Chapter 4: 1 |
3 |
|
Article Summary |
Choose an article from a journal or conference proceedings on the topic of search strategies (e.g, depth-first, breadth-first, etc.). Write a summary on the article based on the established guidelines. |
4 |
|
Practical Exercise |
Run each of the demos of Uninformed Search Methods and the Informed Search Methods on the Virtual Lecture Project website |
3 |
|
Online Class Discussion |
07/12/04 9:00-10:00 pm (ET) -details will be provided via WebCT email |
- |
Module 3: Machine
Learning
|
Assignment |
Description |
Points |
|
Text |
Chapter 18 & 20 |
- |
|
Text Problems |
Chapter 18: 1, 2, 3 / Chapter 20: none |
3 |
|
Article Summary |
Choose an article from a journal or conference proceedings on the topic of machine learning. Write a summary on the article based on the established guidelines. |
4 |
|
Practical Exercise |
Download a freeware neural network package (check here or here for examples). After installing the software run the example data file that is included with the software. Take a screen shot of the results and paste the screen shot into a Word document. |
3 |
|
Online Class Discussion |
07/26/04 9:00-10:00 pm (ET) -details will be provided via WebCT email |
- |
Module 4:
Knowledge-based Systems
|
Assignment |
Description |
Points |
|
Text |
Chapter 10 & 19 |
- |
|
Text Problems |
Chapter 10: 1 / Chapter 19: 2 |
3 |
|
Article Summary |
Choose an article from a journal or conference proceedings on the topic of expert systems. Write a summary on the article based on the established guidelines. |
4 |
|
Practical Exercise |
Run the available expert system demos on the Acquired Intelligence website. Save a screen shot of each and save in a Word file. |
3 |
|
Online Class Discussion |
08/09/04 9:00-10:00 pm (ET) -details will be provided via WebCT email |
- |
Module 5: Reasoning
with Uncertainty
|
Assignment |
Description |
Points |
|
Text |
Chapter 13 & 14 |
- |
|
Text Problems |
Chapter 13: 6 / Chapter 14: 1 |
3 |
|
Article Summary |
Choose an article from a journal or conference proceedings on the topic of Bayesian reasoning. Write a summary on the article based on the established guidelines. |
4 |
|
Practical Exercise |
Download a freeware Bayesian network package. After installing the software run the example data file that is included with the software. Take a screen shot of the results and paste the screen shot into a Word document. |
3 |
|
Online Class Discussion |
08/23/04 9:00-10:00 pm (ET) -details will be provided via WebCT email |
- |
Course Project
The purpose of the course project is for the student to demonstrate an
understanding of AI techniques and concepts. The student will write a 20 page
report on the current and future research activities on any of the topics
discussed in the course. The report will be based primarily on your review and
analysis of at least three research papers from one of the recognized
scientific/technical journals (e.g., ACM, IEEE, Science, etc.). The project
report is worth 25% of a student’s final grade. The report will include the
following:
- An overview of the topic
- Existing approaches and active research areas
- Outstanding problems and potential approaches
- Future research in the area
- References used in the paper (in APA format)
Project Deliverables
- Project Plan - The
project plan will be limited to one page and will include a description of
the proposed topic that will be the subject of the project report. The
project plan will be reviewed by the instructor and comments and
recommended modifications will be provided as necessary. The project plan
must be approved by the instructor before the student begins work on the
report. The project plan is worth 5% of a student’s final grade.
- Project Report - The
final deliverable will be the 20 page report. The project report is worth
20% of a student’s final grade.
Instruction Methods
and Tools
- Questions and comments for the instructor should be submitted via
e-mail. Any questions that are relevant to the class as a whole may be
forwarded to the other students in the class by the instructor unless the
student specifically requests that the question or comment remain in
confidence.
- All class assignments must be submitted via ESET. The modules
should be submitted as a single zip file (all assignments included in the
single zip file). Other deliverables may be submitted in PDF, ZIP, ASCII
text, postscript, and Microsoft Word. You must submit each assignment to
the correct location within ESET.
- Scheduled online class discussions will be conducted utilizing WebCT. The discussions will provide an opportunity for
students to ask questions and provide items of interest regarding the
current course topic. The online
discussions will function primarily as group “office hours” and not as
lecture periods. Participation in
the online discussions is optional.
Examination
The student will complete a comprehensive final examination during the final
week of the semester. Students may use any available materials in completing
the examination, but all sources must be properly cited in the text and
correctly referenced in a bibliography at the end of the document.
Grading Criteria
Achievement of the course objectives by student will be assessed using the
following:
|
Project Plan |
5% |
|
Module 1 |
10% |
|
Module 2 |
10% |
|
Module 3 |
10% |
|
Module 4 |
10% |
|
Module 5 |
10% |
|
Course Project |
20% |
|
Final Exam |
25% |
|
A |
94 - 100 |
|
A- |
90 - 93 |
|
B+ |
87 - 89 |
|
B |
84 - 86 |
|
B- |
80 - 83 |
|
C+ |
77 - 79 |
|
C |
74 - 76 |
|
C- |
70 -73 |
|
F |
<70 |
Course Policies
- All GSCIS
course policies will be strictly enforced.
- The student must notify the instructor of any circumstances that
would interfere with the completion of an assignment prior to the due date
(NOTE: No late assignments will be accepted
without the prior permission of the instructor).
- Students are encouraged to discuss and share information pertaining
to this course. However, all submitted work must be original and must be
your own.
- The final grade in this class will be based on all the material
that is received by the last day of the term (September 10, 2004).
Copyright © 2004 James Cannady, Ph.D.