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Institut für Elektrische Energietechnik
Logo Institut für Elektrische Energietechnik
Institut für Elektrische Energietechnik
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IEET > Personal > Honorarprofessor > Prof. Dr.-Ing. Roland Harig

Prof. Dr.-Ing. Roland Harig

Honorarprofessor

Kontakt

Prof. Dr.-Ing. Roland Harig
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Sprechzeiten
nach Vereinbarung
Harburger Schloßstraße 36,
21079 Hamburg
Gebäude HS36, Raum C2 1.009

Frühere Tätigkeit

bis 03/2015
Leiter des Forschungsbereichs Optische Messtechnik (Infrarotmesstechnik) am Institut für Messtechnik / TUHH

Publikationen

TUHH Open Research (TORE)

2012

2011

2008

Lehrveranstaltungen

Stud.IP
link to course in Stud.IP Studip_icon
Seminare.EIM: Deep Reinforcement Learning (DSBS, CSMS, IIWMS, TMBS, IMPICS)
Semester:
SoSe 24
Course type:
Seminar
Lecturer:
Dr. rer. nat. Pradeep Banerjee
Description:
This course is a basic introduction to Deep Reinforcement Learning (RL). In RL, an agent learns to make sequential decisions by interacting with an environment to maximize some notion of reward. Deep RL combines RL and deep learning, in that neural networks are used to represent the agent's value functions or decision making policies, enabling the handling of complex input spaces such as images or sensor readings. This approach has led to significant advancements in tackling problems such as playing video games, robotics control, and autonomous driving. As a result, expertise in RL constitutes a significant advantage in the industrial job market. By the end of the seminar, it is expected that students will gain proficiency in designing their own RL algorithms, enabling them to apply it to different areas such as robotics, recommendation systems, gaming, etc. to name a few, and also comprehend current literature in the field.
Participants:
The seminar is aimed at all Bachelor- and Master- level students in the Informatik and the Techno-Mathematik courses. A maximum of 12 students can participate in the seminar.
Pre-requisites:
As a prerequisite, this seminar will assume familiarity with probability, linear algebra, and programming in Python.
Learning organisation:
The seminar is divided into six blocks (following an introductory session), each lasting two weeks. Every block consists of the following components: * Week 1: Preparation of a presentation using prescribed sources (book chapters, video lectures, scientific articles). * Week 2: Presentations by 2 participants, each lasting 25 minutes based on a topic assigned to each participant in the first session of the seminar.
Area classification:
Studiendekanat Elektrotechnik, Informatik und Mathematik
Stud.IP informationen about this course:
Home institute: Studiendekanat Elektrotechnik, Informatik und Mathematik (E)
Registered participants in Stud.IP: 11
Documents: 3
TU Hamburg
Institut für Elektrische Energietechnik (ieet) E-6
Prof. Dr.-Ing. Christian Becker
Harburger Schloßstraße 36
21079 Hamburg
E-Mail : ieet(at)tuhh.de
Tel : +49 40 42878 3213
Fax : +49 40 42878 2382
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