Artificial Intelligence Assoc. Prof. Abdulwahab
Description: Artificial Intelligence Assoc. Prof. Abdulwahab AlSammak Course Information Course Title: Artificial Intelligence Instructor : Assoc. Prof. Abdulwahab AlSammak Email : Sammakagmail.com Course Material :
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slide1. Artificial Intelligence Assoc. Prof. Abdulwahab AlSammak<br>
slide2. Course Information Course Title: Artificial Intelligence
Instructor : Assoc. Prof. Abdulwahab AlSammak
Email : Sammaka@gmail.com
Course Material : http://www.mediafire.com/?ygl6b6y653edd
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Course Grading:
Midterm Exam 25
Assignments 10
Lab. & Tutorial 15
Final Exam 75<br>
slide3. References : Textbooks 1. "Artificial Intelligence", by Elaine Rich and Kevin Knight, (2006), McGraw Hill companies Inc., Chapter 1-22, page 1-613.
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2. "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig, (2002), Prentice Hall, Chapter 1-27, page 1-1057.<br>
slide4. 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.<br>
slide5. 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.<br>
slide6. 7. Natural Language Processing : ( 2 weeks)
Introduction, Syntactic processing , Semantic and Pragmatic analysis.
8. Prolog Programming ( 5 weeks in the Lab)<br>
slide2. Course Information Course Title: Artificial Intelligence
Instructor : Assoc. Prof. Abdulwahab AlSammak
Email : Sammaka@gmail.com
Course Material : http://www.mediafire.com/?ygl6b6y653edd
Â
Course Grading:
Midterm Exam 25
Assignments 10
Lab. & Tutorial 15
Final Exam 75<br>
slide3. References : Textbooks 1. "Artificial Intelligence", by Elaine Rich and Kevin Knight, (2006), McGraw Hill companies Inc., Chapter 1-22, page 1-613.
Â
2. "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig, (2002), Prentice Hall, Chapter 1-27, page 1-1057.<br>
slide4. 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.<br>
slide5. 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.<br>
slide6. 7. Natural Language Processing : ( 2 weeks)
Introduction, Syntactic processing , Semantic and Pragmatic analysis.
8. Prolog Programming ( 5 weeks in the Lab)<br>