Assoc. Prof. Abdulwahab AlSammak

Course Information Course Title: Artificial Intelligence Instructor : Assoc. Prof. Abdulwahab AlSammak Course Material : Course Grading: Midterm Exam25 Assignments10 Lab. & Tutorial 15 Final Exam75

References : Textbooks 1. "Artificial Intelligence", by Elaine Rich and Kevin Knight, (2006), McGraw Hill companies Inc., Chapter 1-22, page "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig, (2002), Prentice Hall, Chapter 1-27, page

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)