Valid from: Spring 2019
Decided by: Professor Thomas Johansson
Date of establishment: 2019-09-12
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
Definition of project Implementation of project Presentation of project
Pure project course
Type of instruction: Project. Pure project course
Examination formats: Written report, seminars given by participants
Grading scale: Failed, pass
Examiner:
Admission requirements: PhD student at an engineering faculty
Assumed prior knowledge: Knowledge on reinforcement learning
Selection criteria: None
Project addendum to the course "Study Circle in Reinforcement Learning
Course coordinators:
Web page: http://www.control.lth.se/education/doctorate-program/study-circle-in-reinforcement-learning/