Machine Learning: Evolutionary Algorithms

Evolutionary Algorithms are randomized optimization methods, inspired by principles of biological evolution. Such algorithms apply the principle of "survival of the fittest" to the solution of technical problems. The resulting search heuristics are widely and generically applicable to a wide variety of application problems. They are conceptually simple and often easy to implement. Evolutionary search is often applied to the approximate solution of hard optimization tasks for which efficient problem-specific solvers are not available.

The course starts out with a basic model of an evolutionary algorithm. Departing from this model students will learn about various aspects of evolutionary optimization on discrete and continuous search spaces, from which a systematic taxonomy of modular components will be developed.

The course consists of a two hours/week lecture and an accompanying two hours/week practical course. The course will be in English.

Lecturers

Details

Course type
Lectures
Credits
6 CP
Term
Winter Term 2016/2017

Dates

Lecture
Takes place every week on Friday from 10.15 to 11.45 in room NB 3/57.
First appointment is on 21.10.2016
Last appointment is on 10.02.2017
Exercise
Takes place every week on Monday from 12.15 to 13.45 in room NB 3/57.
First appointment is on 24.10.2016
Last appointment is on 06.02.2017

Requirements

The course is designed for Master students of the Angewandte Informatik program. The lecture "Mathematics for Modeling and Data Analysis" is recommended as a background.

About the INI

The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.

Contact

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210

sekretariat@ini.rub.de
www.ini.rub.de