Hauptinhalt
Topinformationen
Education Working Group Remote Sensing and Digital Image Analysis
Dr. rer. nat. Thomas Jarmer
Lehrveranstaltungen
Sommersemester 2025
Wintersemester 2024/25
Sommersemester 2024
Wintersemester 2023/24
Deep reinforcement learning
Allgemeine Informationen
- Veranstaltungsart
- Seminar
- Semester
- SoSe 2022
- ECTS-Punkte
- 8
- Veranstaltungsnummer
- 8.3487
- Details
- Link zur Veranstaltung in StudIP
Dozent*innen
Tutor*innen
Beschreibung
The course 'Deep Reinforcement Learning' teaches students (1) Basics of Reinforcement Learning (~Chapter 1-7 of 'Reinforcement Learning: An Introduction' by Barto&Sutton), (2) covers all important and major (recent) algorithms that combine Reinforcement Learning with Deep Learning for function approximation (including REINFORCE, A2C, A3C, TRPO, PPO, DDPG, TD3, SAC), (3) provides an overview over some major topics of current DRL research and applications, including topics like MARL, Language Emergence, Distributed RL, GamePlay, World Models, etc, and finally (4) accompanies students on creating their own DRL project. The course is graded based on an exam and the final project, furthermore 4 successful homework submissions are required. The course is offered entirely in a hybrid manner, offering participation also to students from the COSMOS program.
Studienbereiche
- Cognitive Science > Bachelor-Programm
- Cognitive Science > Master-Programm
- Cognitive Science > Promotionsprogramm
Modulzuordnungen der Veranstaltung
- Bachelor of Science Informatik > CS-BWP-AI - Künstliche Intelligenz gültig ab WiSe 2019/20
- Bachelor of Science Mathematik > CS-BWP-AI - Künstliche Intelligenz gültig ab WiSe 2019/20
- Bachelor of Science Cognitive Science > CS-BWP-AI - Künstliche Intelligenz gültig ab WiSe 2019/20
- Master of Science Mathematik > CS-BWP-AI - Künstliche Intelligenz gültig ab WiSe 2019/20
- Bachelor of Science Informatik > CS-BWP-MCS - Methoden der Kognitionswissenschaft gültig ab WiSe 2019/20
- Bachelor of Science Mathematik > CS-BWP-MCS - Methoden der Kognitionswissenschaft gültig ab WiSe 2019/20
- Bachelor of Science Cognitive Science > CS-BWP-MCS - Methoden der Kognitionswissenschaft gültig ab WiSe 2019/20
- Master of Science Mathematik > CS-BWP-MCS - Methoden der Kognitionswissenschaft gültig ab WiSe 2019/20
- Bachelor of Science Informatik > CS-BWP-NI - Neuroinformatik gültig ab WiSe 2019/20
- Bachelor of Science Mathematik > CS-BWP-NI - Neuroinformatik gültig ab WiSe 2019/20
- Bachelor of Science Cognitive Science > CS-BWP-NI - Neuroinformatik gültig ab WiSe 2019/20
- Master of Science Mathematik > CS-BWP-NI - Neuroinformatik gültig ab WiSe 2019/20
