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Technology of Experts Systems

Spring 2006

 

last updated: 2006/03/22

1. Goal of Course

This course is provide study by students of features of architecture of expert systems, methods and tools for development of expert systems, skill to develop small study expert system. Course includes 16 lectures and 8 practical works.

 

2. Textbooks

* It use the presentation materials. You can download on the webboard.

* Contents of lectures:

Introduction. Goals of development of expert systems

Structure of expert system

Knowledge representations in expert systems

    1-first logic

Rules

Frames and semantic networks

Methods of solving of tasks in expert systems

    Search in state space

    Proof

    Tree solving

    Probabilistic reasoning

Development of expert systems

    Conditions for efficient use of Expert Systems

    Steps of development of Expert System

    Features of architectures of Expert Systems

Tools for development of expert systems

    Classification

    Expert shells. ESWin, Exsys,

Prolog

Lisp

CLIPS

    Platform G2

Knowledge acquisition and discovery

    Methods of knowledge acquisition without computer

    Machine learning

    Induction

Hybrid expert systems

 

Condition of passing of midterm exam selection of task for development of study expert system, tool for it, start of implementation of expert system 

 

Condition of passing of final exam implementation of study of expert system

 

3. Instructor

Name

Andrey Gavrilov  (Russia)

Contact Information

Tehephone : 031-201-2493
E-mail : avg@oslab.khu.ac.kr
Office :

Electronic & Information Building #B08

_material    

4. Tentative Schedule (tentative)

Kind

Title

Lecture 1

Introduction

Lecture 2

Knowledge representation in expert systems

Lecture 3

Methods of solving of tasks in expert systems Search in state space

Lecture 4

Proof

Lecture 5

Decision trees

Lecture 6

Probabilistic reasoning

Lecture 7

Conditions for efficient use of Expert Systems

Lecture 8

Steps of development of Expert System

Colloquium 1

Characteristics and features of architectures of Expert Systems

Exam

MIDTERM EXAM

Lecture 9

Expert shells. ESWin, Exsys

Lecture 10

Prolog

Lecture 11

Lisp

Lecture 12

CLIPS

Lecture 13

Platform G2

Lecture 14

Methods of knowledge acquisition without computer

Colloquium 2

Machine learning

Lecture 15

Induction

Lecture 16

Hybrid expert systems

Colloquium 3

Presentations 1

Presentations 2

Presentations 3

Presentations 4

Presentations 5

Term of presentation of students:

Development of Expert System in any determined area for solving of any determined task.

Possible tools for implementation ESWin, CLIPS, Prolog, Lisp

Exam

FINAL EXAM

You can download here:

 

5. Grading Policy

Midterm

Final

Project  (Homework and presentation)

Total

20%

40%

40%

100%

 

5. Suggested reading

  1. Biondo S.J., Fundamentals of Expert Systems Technology:  Principles and Concepts, Ablex, Norwood, NJ, 1990.
  2. Bradshaw, J. (Ed.) Software Agents. Cambridge, MA: MIT Press (1997).
  3. Cawsley Alison. Databases and Artificial Intelligence. Artificial Intelligence Segment. Electronic book.
  4. Giarrantano J.C., Riley G.D. Expert Systems: Principles and programming, PWS Publishing, Boston, 1993.
  5. Harmon P. et al. Expert Systems: Tools and Applications.
  6. Honavar, V. & Uhr, L. (Ed.) Artificial Intelligence and Neural Networks: Steps Toward Principled Integration. San Diego, CA: Academic Press (1994).
  7. Hu D. C/C++ for Expert Systems. Management Information Source, Portland, OR, 1989.
  8. Ignizio J.P. Introduction to Expert Systems: The Development and implementation of Rule-Based Expert Systems. McGraw-Hill, 1991.
  9. Jackson P. Introduction to Expert Systems. Addison Wesley, Publishing Company, Inc. (1998).
  10. Jones M.T. AI application Programming. Charles River Media, Inc., Hingham, Massachusetts (2003).
  11. Liebovitz J. The handbook of Applied Expert Systems. (Electronic book is available).
  12. Luger G.F. Artificial Intelligence. Structures and Strategies for Complex Problem Solving. Addison Wesley  (2002). (Electronic content of separate parts is available).
  13. Merritt D. Building Expert Systems in Prolog. Springer-Verlag, 1989.
  14. Minsky, M. Society of Mind. New York: Basic Books (1986).
  15. Firebaugh, Morris W. Artificial Intelligence: A Knowledge-Based   Approach. PWS-Kent, Massachusetts, 1989.
  16. Negnevitsky M. Artificial Intelligence. A guide to intelligent systems. Addison-Wesley, 2005.
  17. Nilsson, N., Principles of Artificial Intelligence, San Francisco: Morgan Kaufmann (1980).
  18. Newell, A. Unified Theories of Cognition. Cambrdge, MA: Harvard University Press (1990).
  19. Nicolopoulos    Expert systems, 1997.
  20. Poole D., Mackworth A., Goebel R. Computational Intelligence. Logical Approach. Oxford University Press, NY, 1998. (Selected parts are available in electronic version).
  21. Russel, S. & Norvig, P., Artificial Intelligence - a modern approach. Englewood Cliffs, NJ: Prentice Hall (2002). (Electronic content of separate parts is available).
  22. Siler W., Buckley J.J. Fuzzy Expert Systems and Fuzzy Reasoning. 2004.
  23. Sowa J. Knowledge Representation: Logical, Philosophical and Computational Foundation. Pacific Grove, CA: Brooks/Cole (2000).

 

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