No formal requirements.
The course builds on concepts from the bachelor courses Symbolic AI and Machine Learning. Students are expected to program in Python.
Reinforcement learning is a part of machine learning that focuses on agents interacting in an environment, learning which actions to take in order to maximize some kind of reward. The field is rapidly growing, with a wide range of applications in games, robotics, and general decision-making. This course provides a broad introduction to the fundamental (tabular) concepts of Reinforcement Learning. A large part of the course focuses on acquiring hands-on practical experience with applying reinforcement learning algorithms.
After this course, the students are able to:
Understand the fundamental concepts that Reinforcement Learning is based on.
Characterize and differentiate between different fundamental approaches to Reinforcement Learning.
Understand the challenges of using Reinforcement Learning in practice, and current advanced solutions to such challenges.
Be able to apply various types of Reinforcement Learning methods in various environments of varying difficulty.
You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudymap will automatically be displayed in MyTimetable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Pleas note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.
mode of instruction
Written examination with closed questions (50%)
The final grade for the course is established by determining the weighted average. However, both partial grades need to be above the passing margin. There is an opportunity to retake the exam.
The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.
Sutton & Barto, Reinforcement Learning: An Introduction, 2nd edition. Available for free from http://incompleteideas.net/book/the-book.html
Plaat, Learning to Play, 1st edition. Available for free from https://learningtoplay.net/
From the academic year 2022-2023 on every student has to register for courses with the new enrollment tool MyStudymap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.
Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.
Extensive FAQ on MyStudymap can be found here.
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