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School of Science and Technology

Reinforcement Learning, 3 Credits

Örebro University offers a course in Reinforcement Learning. The course provides a general introduction both in theory and practice.

Förstärkt inlärning

Reinforcement Learning (RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences. The course is part of the education initiative Smarter at Örebro University.

The course provides a general introduction to Reinforcement Learning in theory and practice. The following items are covered:

  • Basic concepts of Reinforcement Learning.
  • Formalization of Reinforcement Learning tasks, environments and agents.
  • Basic Reinforcement Learning algorithms for finite systems.
  • Basic Reinforcement Learning algorithms for continuous action spaces.
  • Basics of deep Reinforcement Learning algorithms.
  • Practical aspects of using Reinforcement Learning for control of real-world systems.

The course is designed as a distance learning course with a few compulsory activities. It consists of a series of online lectures, group discussions, compulsory independent study exercises and seminar presentations and a case-based learning task.

  • First class (official start): 13 March 2019, 09:00–12:00
  • Second class (follow-up): 16 April 2019, 09:00–12:00
  • Last class (course completion): 28 May 2019, 09:00–12:00

Please note that the course is taught in English.

This contract education initiative is aimed at working professionals with a higher education qualification of 180 credits earned at the first cycle (bachelor's level) with computer science/computer technology as the main field of study, or alternatively a higher education qualification of 180 credits earned at the first cycle (bachelor's level) in e.g. computer technology/computer science/systems science (which includes computer programming).

In addition, English B/English 6 is required.

The course is free of charge.

The application is closed.

Coordinator of Smarter and professional education in AI

Johan Axelsson

Title: Contract Education Coordinator School/office: Communication and Collaboration

Profile page: Johan Axelsson

Email:

Phone: +46 19 303211

Room: T2201

Johan Axelsson

Course administrator

Jenny Tiberg

Title: Study and Research Administrator School/office: School of Science and Technology

Profile page: Jenny Tiberg

Email:

Phone: +46 19 303320

Room: T1109

Jenny Tiberg