In the project, you will gain practical experience with Learning Architectures for Artificial Intelligence in simulated environments, apply neural networks, and Human-Brain inspired approaches (eye-movements, visual search, attention-based mechanisms, symbolic reasoning) to learn and produce complex purposeful actions in the context of one of the following environments on your choice [1-8]. Advanced students will get a chance to participate in AI competitions, e.g. [9]
[1] Atari: https://youtu.be/XjsY8-P4WHM?t=48
[2] Flatlan trains: https://www.aicrowd.com/challenges/flatland-challenge
[3] Pommerman: https://www.pommerman.com
[4] Montezuma Revenge: https://gym.openai.com/envs/MontezumaRevenge-v0
[5] Doom: http://vizdoom.cs.put.edu.pl
[6] Character Control (PFNN): https://youtu.be/Ul0Gilv5wvY
[7] Character Control (DeepMimic) https://youtu.be/vppFvq2quQ0
[8] Challenges: https://www.aicrowd.com/challenges
[9] Microsoft Research AI challenge winners: https://twitter.com/MSFTResearch/status/1099006255857713153
In case this would not find enough interest for a team project, this project proposal would be also offered (in reduced/modified form)
[x] as individual project
[x] as project for 2-3 students
- Introduction to Neural Networks or Advanced Neural Networks courses.
- Python or C++ ( > 1 year).
Modul | Veranstaltung | Leistungen | |
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39-M-Inf-GP Grundlagenprojekt Intelligente Systeme | Gruppenprojekt | unbenotete Prüfungsleistung
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Studieninformation |
Die verbindlichen Modulbeschreibungen enthalten weitere Informationen, auch zu den "Leistungen" und ihren Anforderungen. Sind mehrere "Leistungsformen" möglich, entscheiden die jeweiligen Lehrenden darüber.