Course Syllabus for

Project in Reinforcement Learning
Projekt i Reinforcement Learning

FRT210F, 3 credits

Valid from: Spring 2019
Decided by: Professor Thomas Johansson
Date of establishment: 2019-09-12

General Information

Division: Automatic Control
Course type: Third-cycle course
Teaching language: English


To give the students practical experience of the development of a reinforcement learning application


Knowledge and Understanding

For a passing grade the doctoral student must be able to implement a working reinforcement learning system

Competences and Skills

For a passing grade the doctoral student must - be able to program in a language suitable for reinforcement learning implementation

Judgement and Approach

For a passing grade the doctoral student must - show compeketence in implementation of reinforcement learning

Course Contents

Definition of project Implementation of project Presentation of project

Course Literature

Pure project course

Instruction Details

Type of instruction: Project. Pure project course

Examination Details

Examination formats: Written report, seminars given by participants
Grading scale: Failed, pass

Admission Details

Admission requirements: PhD student at an engineering faculty
Assumed prior knowledge: Knowledge on reinforcement learning
Selection criteria: None

Further Information

Project addendum to the course "Study Circle in Reinforcement Learning

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page:

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