Master Seminar: Methods of Modern Reinforcement Learning
IMPORTANT:
Seats are limited and the registration is managed via Moodle. The course "Master-Seminar: Methods of Modern Reinforcement Learning" will be available for application from September 15 to October 20, 2020. Seats will be allocated in first-come, first-serve manner, Master's students "Angewandte Informatik" will be treated with priority.
When registering, include your current program in the comment field (e.g., "Master Angewandte Informatik").
Reinforcement Learning (RL) describes the highly active and diverse field of learning optimal behavior from interactions with a changing environment, e.g. achieving expert level performance in computer games just by playing them. Conceptually, RL is considered to lie between supervised and unsupervised machine learning approaches and makes use of techniques from both fields.
In this course, you will get to know the tools of modern RL that led to the 2013 breakthrough result of learning to play computer games at super-human level from visual input only. Afterwards, recent and significant improvements to the method as well as current results will be discussed by directly working with the relevant research papers.
After the successful completion of this course, the students
- understand the framework and basic methods for reinforcement learning,
- understand core challenges of the field, and
- will be able to contextualize current publication with respect to those challenges.
Lecturers
Details
- Course type
- Seminars
- Credits
- 3
- Term
- Winter Term 2020/2021
Dates
- Seminar
-
Takes place
every week on Thursday from 10:15 to 11:45.
First appointment is on 29.10.2020
Last appointment is on 12.02.2021
Requirements
We expect a solid level of mathematics as taught in the Applied Computer Science Bachelor‘s. Tools commonly used in machine learning are
- basic probability theory/statistics (expectations, variance, foundational distributions and densities, markov chains)
- linear algebra (matrices, vectors, eigenvalues/eigenvectors)
- calculus (functions, derivatives/gradients, simple integrals)
The course material is in English, the course language will be English (default) or German – depending on the students.
The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through 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 approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany
Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210