EGE UNIVERSITY GRADUATE SCHOOL OF NATURAL AND APPLIED
SCIENCES COMPUTER ENGINEERING
DEPARTMENT 
20172018 SPRING SEMESTER 
Course 
624 INTELLIGENT SYSTEMS
(3+0) 

Instructor 
Prof. Dr.
Aybars UĞUR 

Course Place and Time 
EGE University Computer Engineering Department B1 Room (Tuesday, 13:1516:00) 

Learning Outcomes 


Description 
Introduction to Intelligent Systems, Artificial Neural Networks, Evolutionary Computation, Fuzzy Logic, Expert Systems, Hybrid Intelligent Systems, Fuzzy Expert systems, Neural Expert Systems, Neurofuzzy Systems, Evolutionary Neural Networks. 

Syllabus 


Textbook 
Michael Negnevitsky, “Artificial Intelligence : A Guide to Intelligent Systems (3rd Edition)”, Addison Wesley, 2011. 

Reference Books 
Also Sample Papers will be given. 

Links 
http://en.wikipedia.org/wiki/Hybrid_intelligent_system http://www.slideshare.net/ikensolutions/hybridintelligentsystemspresentation 

Prerequisites 
Artificial Intelligence Basics: Problem solving, state space search, machine learning principles, pattern recognition, fundamentals of computer vision. Basic knowledge of probability, statistics, calculus and linear algebra. 

Grading 
Midterm Activities (50%) ·
Project (+ Paper)
(30%) ·
Presentation 1 (10%) ·
Presentation 2 (10%) ·
TakeHome
 Final Exam (50%) For the TakeHome and reports, students will be
allowed a total of 5 (five) late days; each additional late day will incur a
10% penalty. 