At the end of this course, the students; 1) Be informed of Knowledge representation and reasoning. 2) Know syntax, semantics, and proof theory (deductive inference) of propositional logic. 3) Apply first-order predicate logic. 4) Have knowledge of uncertainty and probabilistic reasoning. 5) Recognize expert systems.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
none
COURSE DEFINITION
Knowledge representation and reasoning. Syntax, semantics. Proof theory (deductive inference) of propositional logic. First-order predicate logic. Uncertainty. Probabilistic reasoning. Expert systems.
COURSE CONTENTS
WEEK
TOPICS
1st Week
Knowledge representation and reasoning.
2nd Week
Knowledge representation and reasoning.
3rd Week
Knowledge representation and reasoning.
4th Week
Syntax, semantics.
5th Week
Syntax, semantics.
6th Week
Syntax, semantics.
7th Week
Syntax, semantics.
8th Week
Mid-term
9th Week
Proof theory (deductive inference) of propositional logic. First-order predicate logic.
10th Week
Proof theory (deductive inference) of propositional logic. First-order predicate logic.
11th Week
Uncertainty.
12th Week
Probabilistic reasoning.
13th Week
Expert systems.
14th Week
Expert systems.
RECOMENDED OR REQUIRED READING
1. Russell S., Norvig P. Artificial Intelligence: A Modern Approach, Prentice Hall, 2003, Second Edition, ISBN: 9780137903955