This
course deals with introduction to artificial intelligence, knowledge systems,
documentation, programming methods, applications such as recognizing a model,
proving theories, research methods (blind search, depth-first search,
cross-search first, limited-depth search, iterative search, random search, bait
search , Climbing the Mountain), Human Language Understanding, Simulated
Understanding, Expert Systems Programming Languages, Problem Solving,
Introduction to “Prolog” or “Lisp” Programming Language.
Intended learning outcomes
1. Know
the basic concepts of artificial intelligence
2.
Defines branches, methodologies and research methods for artificial
intelligence
3.
Explain the applications of artificial intelligence and understand the
structure of each application.
4.
Distinguish between traditional languages and artificial intelligence
languages
5.
Explains how to write a program in the parlog language
Teaching and learning methods
1.
Lectures
2.
Laboratory activities
3.
Panel discussions and presentations
4. Case
studies such as AI applications.
5. The
ability to collect information and research
Methods of assessments
midterm
exam 30%
practical
exam 10%
final
exam 60%
Total
100%
References
Course
notes
Artificial
Intelligence: A Handbook of Intelligent Systems