DCIS 760 – Artificial Intelligence and Expert Systems (3 credits)

Fall Cluster 2002 (September 13, 2002 - February 12, 2003)



Professor Jim Cannady
(954) 262-2085


Course Description

Theory of, and major approaches to, artificial intelligence. Topics include knowledge representation, heuristic search, artificial neural networks, machine learning, intelligent agents, and knowledge-based systems.


Recommended Texts

Title: Artificial Intelligence: A Modern Approach
Author: Stuart J. Russell, Peter Norvig
Publisher: Prentice Hall
ISBN: 0-13-103805-2



Exit Competencies

Upon the successful completion of this course, the student should possess the ability to apply the principles of artificial intelligence in the design and development of solutions for complex information systems.


Course Content Overview

§         Introduction to Artificial Intelligence

§         Intelligent Agents

§         Machine Learning

§         Neural Networks

§         Machine Evolution

§         Fuzzy Logic

§         Knowledge-based Systems

§         Planning/Searching

§         Case-based Reasoning

§         Reasoning with Uncertain Information

§         Future Trends


Instruction Methods and Tools

The following on-line tools will be used in the course:


§         ESET - The electronic student /electronic teacher (ESET) web-based interface will be used by the student to submit all course assignments.  The instructor will provide assignment grades through ESET


§         Forums – A general forum will be created for the course under the SCIS Student Forums.  The unmoderated forum will be available for students to discuss course-related activities and issues.


§         Email – Electronic mail will be used in the course by the instructor to notify students of course-related issues and requirements during non-cluster periods.  Students will use email for all questions, concerns, or issues addressed to the instructor during the course.  All correspondences via email will utilize the students NSU email account.  Students should check their NSU email daily.  




1.      Research Pre-proposal (Due 10/13/02)

The student will select a topic of current interest in artificial intelligence research and development and write a research pre-proposal on their topic area. The research pre-proposal must comply with the Pre-Proposal guidelines specified in the Nonexistent Science Foundation Information Technology Research Program.

The purpose of the research pre-proposal is to allow the student to select an appropriate course topic and to begin investigating the topic.



2.      Topic Paper (Due 11/03/02)

The student will write a brief survey paper on their course topic.  The articles referenced in the paper must be primarily from peer-reviewed journals and conference proceedings. Web-based articles should be avoided.  Follow the guidelines for submissions to the ACM Computing Surveys when preparing the document.   The topic paper should be at least 10 single-spaced pages in length.

While the student will be strongly encouraged to submit the final survey paper to a journal or conference for publication, the acceptance or rejection of the paper will not affect the grade for the assignment.  The Topic Paper will be evaluated on thoroughness, completeness and the student’s analysis and understanding of the topic.



3.      Topic Application (Due 12/01/02)

Conduct a thorough analysis of the course topic through the development of a Java-based application that demonstrates some aspect of the topic area.  Your task is to design and develop a prototype system that utilizes artificial intelligence techniques to solve problems in an appropriate domain.

You are required to submit a final report on your application that includes the following:

  1. Identify the problem that you were trying to solve.
  2. Justify the need for an artificial intelligence-based approach to solve the problem.
  3. Discuss the problem solving methodology in detail.
  4. Provide the design specifications for the system
    1. Specify the knowledge representation scheme in detail.
    2. Explain all algorithms and solution strategies that were used.
  5. The results from your tests of the system with appropriate data.
  6. Source code must be included as an appendix to the report.


4.      Class Presentation (Due 12/06/02)

The student will provide a presentation for the class on the subject of their topic application. The presentations will be conducted during the second cluster meeting (December 6-8, 2002). The student will use the following as a guide for the presentation:

·        Overview/Introduction

·        Explanation of key concepts

·        Demonstration of application

·        Additional applications of the technology/Future Trends

·        Conclusion

The student will be evaluated by the instructor based on the quality of the presentation and the ability of the student to present the material effectively to the other students in the class. Hard copies of the presentation must be available for the other students during the presentation.


5.      Research Proposal (Due 02/02/03)

The student write a research proposal on their topic area.  The research proposal must comply with the Full Proposal guidelines specified in the Nonexistent Science Foundation Information Technology Research Program.  The research proposal will be evaluated based on the student’s understanding of the potential research topics in their area, the innovative science that is proposed in the document, and the thoroughness of the proposal.    


Comprehensive Examination (Due 09/29/02)

A comprehensive examination will be provided to the student after the first cluster meeting.  The examination will cover all of the topics covered during the first cluster meeting and will be used to demonstrate the student’s understanding of the core concepts and issues. 



Achievement of the course objectives by students will be assessed using the following:

Comprehensive Exam


Research Pre-proposal


Topic Paper


Topic Application


Class Presentation


Research Proposal



The student’s final grade will be based on the following cumulative scores throughout the semester:


94 -100%


90 - 93%


87 - 89%


84 - 86%


80 - 83%


77 - 79%


74 - 76%


70 - 73%





Course Policies

  1. All SCIS course policies will be strictly enforced.
  2. 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).
  3. All class assignments must be submitted via ESET. The acceptable formats are PDF, ZIP, ASCII text, postscript, and Microsoft Word.
  4. Students are encouraged to discuss and share information pertaining to this course. However, all submitted work must be original and must be your own.

Copyright © 2002 James Cannady