Welcome, Guest . Login . Türkçe
Where Am I: Ninova / Courses / Faculty of Management / END 457E - Sezgisel Arama ve Yapay Zeka
 

END 457E - Heuristic Srch&Artific.Intell.

Course Objectives

1. To introduce a variety of heuristic methods with relevant mathematics and area of application.
2. To give knowledge on developing heuristic algorithms.
3. To provide fundamental information on Artificial Intelligence Techniques.

Course Description

The difficulty levels of many real world problems in business are considered to be NPComplete.
Utilizing conventional opitimization techniques in this type of problems either are
computationally expensive or do not yield to a result. However, utilizing Heuristic Search
algorithms, a near-optimum solution can be found in a short amount of time. This course firstly
provides a detailed introduction to Heuristic Search algorithms.Simulated Annealing, Tabu
Search, Genetic Algorithm, Ant Colony and Swarm Intelligence will be in the focus, but an
overview of other methods will also be given. Secondly, an the concepts of Artificial Intelligence
will be introduced. Additionally, two methods that provide modeling in Artificial Intelligence will
be introduced: Self-Organizing Maps and Fuzzy Logic. Attendees will gain knowledge of where
and how to use heuristic methods in addition to reading about comparisons with classical
algorithms in selected papers

Course Coordinator
Ömer Faruk Beyca
Course Language
English
 
 
Courses . Help . About
Ninova is an ITU Office of Information Technologies Product. © 2024