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Assoc. Prof. Abdulwahab AlSammak
Course Information
 Course Title: Artificial Intelligence
 Instructor : Assoc. Prof. Abdulwahab AlSammak
 Email : [email protected]
 Course Material : http://www.mediafire.com/?ygl6b6y653edd
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Course Grading:
Midterm Exam
Assignments
Lab. & Tutorial
Final Exam
25
10
15
75
References : Textbooks
 1. "Artificial Intelligence", by Elaine Rich and
Kevin Knight, (2006), McGraw Hill companies
Inc., Chapter 1-22, page 1-613.
 2. "Artificial Intelligence: A Modern Approach"
by Stuart Russell and Peter Norvig, (2002),
Prentice Hall, Chapter 1-27, page 1-1057.
Course Content
1. Introduction to AI ( 1 week)
Definitions, Goals of AI, AI Approaches, AI Techniques,
Branches of AI, Applications of AI.
2. Problem Solving, Search and Control Strategies :
( 2 weeks)
General problem solving, Search and control strategies,
Exhaustive searches, Heuristic search techniques,
Constraint satisfaction problems (CSPs) and models .
3. Knowledge Representations Issues, Predicate
Logic, Rules : ( 2 weeks)
Knowledge representation, KR using predicate logic, KR
using rules.
4. Reasoning System - Symbolic , Statistical :
( 2 weeks)
Reasoning - Over view, Symbolic reasoning, Statistical
reasoning.
5. Learning Systems: ( 2 weeks)
Rote learning, Learning from example : Induction,
Explanation Based Learning (EBL), Discovery,
Clustering, Analogy, Neural net and genetic learning,
Reinforcement learning.
6. Expert Systems : ( 2 weeks)
Knowledge acquisition, Knowledge base, Working
memory, Inference engine, Expert system shells,
Explanation, Application of expert systems.
7. Natural Language Processing : ( 2 weeks)
Introduction, Syntactic processing , Semantic and
Pragmatic analysis.
8. Prolog Programming ( 5 weeks in the Lab)