392115 Deep Reinforcement Learning (S) (WiSe 2018/2019)
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Join our weekly meetings on Thursdays 14:30-16:00 at CITEC-1.015.
The seminar focus is on current approaches to deep reinforcement learning [1] as has been explored widely in the last couple of years in the area of learning decisions in computer games [2]. Further, current work extends these approaches to more real-world problems as grasping in robotics [3]. The seminar will give an introduction to the theoretical background of Deep Reinforcement Learning. It will afterward deal with state of the art methods and research literature presenting those methods [4]. Participants are expected to actively participate in the course by presenting selected articles. The seminar aims at comparing different approaches and providing an overview of current evolving principles and questions.
[1] https://deepmind.com/blog/deep-reinforcement-learning
[2] https://youtu.be/XjsY8-P4WHM?t=48s
[3] https://blog.openai.com/learning-dexterity
[4] https://rebrand.ly/DRL
Bibliography
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
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Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-EGMI Ergänzungsmodul Informatik | vertiefendes Seminar 1 | Ungraded examination
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Student information |
| vertiefendes Seminar 2 | Ungraded examination
|
Student information | |
| vertiefendes Seminar 3 | Ungraded examination
|
Student information | |
| vertiefendes Seminar 4 | Ungraded examination
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Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
• regular attendance
• active participation in discussions
• presentation of selected articles,
• writing a report on the presented articles.
- Registered number: 19
- This is the number of students having stored the course in their timetable. In brackets, you see the number of users registered via guest accounts.
- Address:
- WS2018_392115@ekvv.uni-bielefeld.de
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- Coverage:
- 4 Students to be reached directly via email
- Notes:
- Additional notes on the electronic mailing lists
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- Last update basic details/teaching staff:
- Tuesday, June 9, 2020
- Last update times:
- Monday, October 22, 2018
- Last update rooms:
- Monday, October 22, 2018
- Type(s) / SWS (hours per week per semester)
- Seminar (S) / 2
- Language
- This lecture is taught in english
- Department
- Technische Fakultät
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