DRAFT
CMSI 682 KNOWLEDGE-BASED SYSTEMS
Fall 2011 -- 3.0 units
Wednesday 6:30 - 9:30 p.m. -- Doolan 222
Dr. Stephanie E. August -- saugust@lmu.edu
DRAFT
DRAFT
Course Description
DRAFT
Objectives
The primary objective of this course is to introduce the fundamental concepts of knowledgebased systems, focusing on rule-based systems, and to provide experience in designing and
implementing these systems. The secondary objective is to explore the application of
knowledge-based systems to a variety of areas, such as space systems, telecommunications,
business, healthcare, and models of cognition. Among the topics to be covered are: logic and
theorem proving, pattern matching, deduction systems, reaction systems, forward and backward
chaining, knowledge acquisition, uncertainty management, and explanatory interfaces. Students
will have the opportunity to implement a simple knowledge-based system during the course of
the semester using a knowledge-based tool such as CLIPS or JESS.
Recommended (Helpful, but not required)
Knowledge of a higher level programming language, such as Java, C++, Prolog, or Lisp
CMSI 677 Introduction to Artificial Intelligence
Expected Work
Readings prior to lectures and participation in class discussion.
Programming and written homework assignments to reinforce lectures and readings.
Oral presentations on successful applications of knowledge-based system technology (based
upon assigned readings).
Term project (completed on an individual basis) in which the student develops requirements for,
implements, and tests a simple knowledge-based system using CLIPS, JESS, or SOAR.
Exams
Two midterms.
Text and Required Materials
Expert Systems: Principles and Programming. Joseph Giarratano and Gary Riley. 4th ed.
Thomson Course Technology, 2005.
CLIPS expert system language, CLIPS Basic Programming Guide, and CLIPS User's Guide.
These materials are available in electronic form at http://clipsrules.sourceforge.net/.
Supplementary materials as posted on course website or handed out in class.
Additional References
Expert Systems: The Journal of Knowledge Engineering.
Artificial Intelligence. Patrick Henry Winston. 3rd edition. Addison-Wesley, Reading MA,
1992.
Artificial Intelligence. Elaine Rich & Kevin Knight. 2nd edition. McGraw-Hill,
New York, 1991.
Artificial Intelligence: A Modern Approach. Stuart J. Russell and Peter Norvig. Prentice-Hall,
Englewood Cliffs, NJ, 2003.
Introduction to Knowledge Systems. Mark Stefik. Morgan Kaufmann Publisher, Inc., San
Francisco, 1995.
Knowledge-based Systems in Artificial Intelligence. Randall Davis & Douglas B. Lenat.
McGraw-Hill, New York, 1982.
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KNOWLEDGE-BASED SYSTEMS
CMSI 682 Fall 2011
Course Description
Sample Supplemental Readings
Dzierzanowski, J., Hestenes,E., and Lawson, S. 1992. The credit assistant: the second leg in the
knowledge highway for American express. In Proceedings of the fourth conference on
Innovative applications of artificial intelligence (IAAI'92), A. Carlisle Scott and Phillip
Klahr (Eds.). AAAI Press 127-134.
Grossman, L. 2011. 2045: When man becomes immortal. Time, Feb. 10, 2011.
Ibáñez, J. and Delgado-Mata, C. 2011. Adaptive two-player videogames. Expert Systems with
Applications, 38:8, p.9157-9163.doi:10.1016/j.eswa.2011.01.095
It’s a smart world: A special report on smart systems. The Economist, Special Report, Nov. 6,
2010.
Kidd, R.C. and Carlson, R.J. 1992. A truly MAGIC solution. Proceedings of the fourth
conference on Innovative applications of artificial intelligence (IAAI'92), A. Carlisle Scott
and Phillip Klahr (Eds.). AAAI Press 237-247.
Little, J. P. and Gingrich, M. 1992. ADJUDIPRO. Proceedings of the fourth conference on
Innovative applications of artificial intelligence (IAAI'92), A. Carlisle Scott and Phillip
Klahr (Eds.). AAAI Press 249-262.
Tun, N. N., Dong, J. S. and Tojo, S. (2011), A philosophy-driven entity classification and
enrichment for ontology mapping. Expert Systems, 28: 138–166. doi: 10.1111/j.14680394.2010.00544.x
von Lubitz, D,, Wickramasinghe, N. 2006. Networkcentric healthcare and bioinformatics:
Unified operations within three domains of knowledge. Expert Systems with Applications,
30:1, Intelligent Bioinformatics Systems, January 2006, Pages 11-23, ISSN 0957-4174, DOI:
10.1016/j.eswa.2005.09.069. (http://www.sciencedirect.com/science/article/B6V034HBSJX8-3/2/953a77b3abcd66383f02aa3daaedd95b)
Williams, D., Simons, B.C., and Connolly, J. 1996. AdjudiPro; 2.0. Proceedings of the eighth
annual conference on Innovative applications of artificial intelligence (IAAI'96). AAAI
Press 1570-1578.
Grading
Your final grade will be weighted as follows:
Tentative
Project
30%
Midterm #1
20%
Midterm #2
20%
Assignments
15%
Presentations of applied KBS (case study)
15%
Homework will be assigned and graded. As time permits, homework will be reviewed in class
on the due date. When current events related to knowledge-based systems are in the news,
student will have the opportunity to give oral and written reports on the events.
An incomplete will be granted only when the student requesting the incomplete has completed
80% of the coursework, and has at least a B average in the coursework completed.
Refer to the Teaching Philosophy and Course Policies handout for additional information.
Office Hour/Contact Points
Office Hours: Wednesday, 1-4, 5-6 p.m. and by appointment.
Office: Doolan 201b
Phone: (310) 338-5973
Internet: saugust@lmu.edu
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