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THE UNIVERSITY OF TEXAS AT AUSTIN
GRADUATE SCHOOL OF LIBRARY AND INFORMATION SCIENCE
ARTIFICIAL INTELLIGENCE
LIS 385T.15 45075
SPRING 2002 T 6:30-9:30pm; SZB 468
Professor Glynn Harmon
Office: SZB 562D OH: W 2:00-3:00pm
Phone: 471-3972; Fax: 471-3971
[email protected]
I.
COURSE DESCRIPTION
A seminar style overview of the historical development of artificial intelligence, its
current state-of-art, and the potential for super-intelligence. Includes a survey of AI’s
documented history, key players and developmental landmarks, present approaches,
knowledge-based systems (KBS) and their developmental tools, and reference resources.
Focuses on the evaluation of developed AI systems for deployment in information service
and decision support settings.
II.
OBJECTIVES, REQUIREMENTS, AND GRADING
1.
To attain a general understanding of the past development of AI, its present
status, and its future potential. To achieve this objective, requirements include
three brief oral reports on the history of AI, its current status, and its probable
future (30% of course grade—10% per report).
2.
To understand the current major classes of knowledge-based systems, their
applications potential in information services, developmental tools, and the
process of knowledge engineering. Requirements include coverage of the
textbook, acting as a discussion leader on a major KBS approach, and
demonstration of a related developmental tool (30% of grade).
3.
To learn to evaluate emerging and developed AI systems for potential
application in an information service or decision support settings. Requirements
include brief written evaluations of three developed systems (30% of grade).
4.
Active, continuous and constructive participation in class discussions (10% of
grade).
5.
In place one of the first three major requirements above, you may elect to take a
final, open-book exam covering that objective and its requirement(s). That is,
you may opt not to do the required work for any one of the first three objectives
and instead take a written final exam on it (which will count for 30%
of the course grade).
III. REQUIRED TEXTBOOK
1. Negnevitsky, Michael (2002) Artificial Intelligence: A Guide to
Intelligent Systems. NY: Addison Wesley. ISBN: 0201-71159-1
Note the end-of-chapter References and Bibliography, and the Glossary and
Appendix: AI Tools and Vendors.
IV. KEY SUPPLEMENTARY SOURCES
1. Web site of the American Association for Artificial Intelligence
www.aaai.org. We will use this site and its links throughout the course,
especially for its great historical coverage, its bibliographic resources and
tutorials, and its access to software tools and demonstrations.
2. Other useful sites include www.acm.org, www.asis.org,
www.webopedia.interner.com, www.webopedia.com,www.amia.org (note the
Digital Library access), and www.cs.utexas.edu (AI and KBS research groups),
among others.
3. Encyclopedia of Artificial Intelligence 2nd. Ed. PCL Reference Department,
Q 335 E53 1992.
4. PCL stacks (QA 76.76 E95 and neighboring) contain a number of interesting
books and conference proceedings. The instructor maintains a small personal
library of AI, KBS and expert system books, including some classics, which you
may check out.
5. Richardson, John V. (1995) Knowledge-Based Systems for General Reference
Work: Applications, Problems, and Progress. NY: Academic Press. The
instructor has checked out this book for the semester for instructional use.
6. Zick, Laura. (2000) “The Work of Information Mediators: A Comparison of
Librarians and Intelligent Software Agents,” First Monday Vol. 5, No. 5.
May 1, 2000. www.firstmonday.dk.
7. Excerpted chapters from Brown, John S. and Dugrid, Paul (2000) The Social
Life of Information. Boston: Harvard university Press. In First Monday Vol. 5,
No. 4. April 3, 2000. www.firstmonday.dk. A look at the future of AI and
Agents.
8. Be on the lookout for a Scientific American issue on AI, March 2002.
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V.
INSTRUCTIONS FOR COMPLETION OF REQUIREMENTS
1. Oral reports.To attain a general understanding of AI (Objective 1.), please
become familiar with the www.aaai.org portal by browsing through it; also read
the “Springboard” section so that you will know its limitations. Then prepare
for your three brief oral class reports (10 minutes each) by selecting a linked
reading of at least 10 pages for each oral report. Each oral report counts for
10% of the course grade. Grading will be done on the basis of how well it
serves to accomplish the first objective, overall clarity, brevity and coherence,
and recognition of significant landmarks, trends and useful resources. Please
also be prepared to react or comment on the reports of others.


Your first two oral reports should cover the past and/or present of AI,
as well as implications or direct commentary about future prospects.
Examples of such linked sites include (from the AI Overview) “What is
AI?”; “Introduction to the Science of AI”; “AI’s Greatest
Controversies”; “Readings Online” (about 20 articles from which to
select); a description and evaluation of a “Related Web Site”; “AI in the
News” (some 50 articles); or “Careers in AI”. To prepare each of your
oral reports, you should try to provide a composite view of AI’s past
landmarks, present status (state-of-art), and emergent major trends,
insofar as you can. Please be prepared to deliver your first oral report at
the second class meeting, and the second report at the third class
meeting. Although there will be some duplication in the selected
materials, we should be able to capture a picture of the overall AI
landscape very early. You need not prepare handouts or bibliographies
for the class; you may use the computer-projector to point out features of
your selection.
The third oral report should focus on reference resources, which
describe or provide access to bibliographies, useful web sites, journals,
books, encyclopedias, demonstrations, shell or knowledge engineering
software or systems, applications, etc. Third reports are scheduled for
the fourth class meeting.
2. Report on selected KBS. To acquire an understanding of KBSs, we will each
lead a discussion on an assigned chapter in the textbook that covers a given type
of KBS (rule-based expert systems, fuzzy systems, frame-based systems, neural
networks, evolutionary computation, and hybrid intelligent systems) and its
applications and developmental tools. To lead a discussion, you should assume
that everyone has read the chapter. Present a brief (5-10 minute) summary or
tutorial about the system, demonstrate the system and/or one of its
developmental tools or applications (10-15 minutes), then lead a 20 minute
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INSTRUCTIONS (continued)
discussion by presenting one or more challenging discussion questions (you
may draw on the “Questions for Review” at the end of your chapter or derive
your own questions). You need not cover the highly technical or mathematical
aspects of the system or its applications or tools (since we are oriented to its
professional use, rather than its development). Upon concluding your oral
report, please elicit a general discussion about your system,
relevant problems or issues, exciting information service applications, and future
potential of the technology. Take advantage of the textbook’s Appendix or
the AAAI site and other sources to find a web-based demonstration of a tool or
system. You should use the computer/projector to present your online
demonstration of the system and its developmental tool. You need not prepare
class handouts.
In addition to the above discussion leadership, please issue a 1 to 2 page
evaluation or rating of the KBS, its developmental tool, and vendor support. The
evaluation should be intended for use by an information service or decision
support organization or function that you designate, and submitted to the
instructor at the conclusion of your report. You may submit copies to class
members if you wish. Grading: discussion leadership counts for 15% and the
written evaluation for 15% of the course grade (total 30%). Grading criteria
include the oral coverage of the chapter and discussion leadership, and the
apparent suitability of your rating for the application area and context that you
designate.
3.
Evaluation of developed KBS applications. We will review the operation of
a few developed KBSs , such as Ask Jeeves, AIQ (for stock trading), DxPlain
(medical diagnosis), CYC (encyclopedic system),and the Botany Knowledge Base
developed by the group at UT Austin (www.cs.utexas.edu/users/mfkb/RKF/).
Please draft brief written evaluations (1-2 pages each) of the suitability of three
developed systems for purchase, adoption, implementation, and use in
decision-making or information services functions. Such KBS systems should
ultimately be useful in conventional or digital library systems, or in supporting
individual information consumers. It would be helpful to read Laura Zick’s
First Monday paper (item #6 in supplementary Sources above), to look at ALA’s
LITA review formats (www.ala.org), to review the instructor’s published
evaluation of CYC to be handed out, etc. Your written reports will be graded
according to their apparent usefulness for information professionals in a context
that you designate, the adequacy of cost and performance benchmarks that you
employ, rigor, and overall clarity. Each report counts for 10% of the course
grade (30% total).
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INSTRUCTIONS (continued)
4.
Final exam elective. In lieu of completing either requirement 1, 2, or 3 above,
you may elect to take an open book final exam that will cover the topical material
required section that you did not complete. We will discus the nature of the exam
in class. Tentatively, the exam is scheduled for Tuesday,
May 14, 7-10pm (location TBA).
VI.
COURSE CALENDAR
Tuesday
January 15
 Introduction to course
 Textbook and readings
 Review of AAAI site
 Assignment of first oral report topics
January 22
 First oral reports on AAAI web site topic
 Review of KBS movement
 Selection of second oral report topics
 Review of information life cycle applications
January 29
 Second oral reports on AAAI web site topic
 Selection of third oral report topics
 Discussion of historical and future KBS development
February 5
 Third oral reports on AAAI web site topic
 Discussion of textbook, Chapter 1. Conclusions about AI past, present, future
 Assignment of textbook chapters (KBS reports)
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REVISED CALENDAR (continued)
Tuesday
February 12
 Oral report and demo: Rule-based Expert Systems (Chapter 2 of textbook)
 Read Zick,“The Work of the Information Mediator” www.firstmonday.dk, Vol. 5,
Number 5
 Discussion of existing RBS systems
February 19
 Oral Report and demo: RBS Uncertainty management (Chapter 3 of textbook)
 Discussion of existing RBS systems
 Discussion of Zick, “The Work of the Information Mediator”
February 26
 Discussion of Fuzzy expert systems (Chapter 4)
 Oral report and demo: Frame-based expert systems (Chapter 5)
 Discussion of existing FBS
March 5
 Oral report and demo: Neural networks (Chapter 6)
 Discussion of existing neural network systems
March 12
No class—Spring Break!
March 19
 Oral report and demo: Evolutionary computation (Chapter 7)
 Discussion of evolutionary systems
March 26
 Oral report and demo: Hybrid intelligent systems (Chapter 8)
 Discussion of existing hybrid systems
April 2
 Oral report and demo: Case-based reasoning systems (assigned reading)
 Discussion of case-based reasoning systems
 Discussion of Knowledge engineering and data mining (Chapter 9)
 Read Ask Jeeves (www.ask.com)
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REVISED CALENDAR (continued)
Tuesday
April 9
 Discussion of Ask Jeeves strengths and weaknesses.
 Discussion of other developed or emerging systems
 First written evaluation of information service system due (1-2 pages)
 Read about AIQ system (www.aiq.com) site on stock trading system
April 16
 Discussion of AIQ system
 Discussion of other emerging or developed information service systems
 Second written evaluation of information service system due (1-2 pages)
 Read on Botany Knowledge Base (www.cs.utexas.edu/users/mfkb/RKF/)
April 23
 Discussion of Botany KB and other emerging or existing systems
 Third written evaluation of information service system due (1-2pages)
April 30 (last class)
 Concluding discussion
 Briefing on final exam elective
 Course survey
May 14
 Final exam elective (open book)
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