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rudolph:cig_new [2021-10-27 15:32] Marco Pleines |
rudolph:cig_new [2021-10-27 15:36] Marco Pleines [Theses (Abschlussarbeiten)] |
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| * [[staff:nicolas_fischoeder|Nicolas Fischöder]] | * [[staff:nicolas_fischoeder|Nicolas Fischöder]] | ||
| - | ===== Games for Computational Intelligence Research ===== | + | ===== Publications ===== |
| + | |||
| + | === Conference Articles (peer reviewed) === | ||
| + | |||
| + | == 2020 == | ||
| + | |||
| + | * Marco Pleines, Jenia Jitsev, Mike Preuss, Frank Zimmer. [[https://arxiv.org/abs/2004.00567|Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning]]. In CoG 2020 Proceedings, IEEE. Best Paper Candidate. | ||
| + | |||
| + | == 2019 == | ||
| + | |||
| + | * Marco Pleines, Frank Zimmer, Vincent-Pierre Berges. [[http://www.ieee-cog.org/papers/paper_22.pdf|Action Spaces in Deep Reinforcement Learning to Mimic Human Input Devices]]. In CoG 2019 Proceedings, IEEE. | ||
| + | |||
| + | === Competitions === | ||
| + | |||
| + | == 2019 == | ||
| + | |||
| + | * Marco Pleines, Mike Preuss, Jenia Jitsev, Frank Zimmer, Jonathan Indetzki. [[https://youtu.be/P2rBDHBHxcM|Rising to the Obstacle Tower Challenge]]. In CoG 2019 Short Video Competition, IEEE | ||
| + | ===== Theses (Abschlussarbeiten) ===== | ||
| + | |||
| + | === Bachelor Theses === | ||
| + | |||
| + | === Master Theses === | ||
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| + | |||
| + | |||
| + | ===== Teaching ===== | ||
| + | |||
| + | ==== Fachprojekt (technical project) Digital Entertainment Technologies ==== | ||
| + | |||
| + | |||
| + | |||
| + | ==== Project Groups ==== | ||
| + | |||
| + | === PG 642: Verteiltes Deep Reinforcement Learning System zum Trainieren von Game AI === | ||
| + | |||
| + | The goal of this project group is to train agents to play Rocket League using a distributed Deep Reinforcement Learning system. | ||
| + | Training directly on Rocket League comes with many issues. Therefore, the game is reimplemented in Unity. | ||
| + | This raises the challenge of transferring the learned behavior in Unity to Rocket League, which is called a sim-to-sim transfer. | ||
| + | As this project is still ongoing, there are no outcomes to be presented yet. | ||
| + | |||
| + | |||
| + | |||
| + | |||
| + | |||
| + | ===== Links ===== | ||
| + | |||
| + | ==== Games for Computational Intelligence Research ==== | ||
| * [[https://github.com/Baekalfen/PyBoy|PyBoy]] | * [[https://github.com/Baekalfen/PyBoy|PyBoy]] | ||
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| * [[https://sites.google.com/view/arena-unity/home/learning-environments|Arena]] | * [[https://sites.google.com/view/arena-unity/home/learning-environments|Arena]] | ||
| - | ===== Publications ===== | ||
| - | |||
| - | === Journal Articles === | ||
| - | |||
| - | === Conference Articles (peer reviewed) === | ||
| - | |||
| - | === Technical Reports === | ||
| - | |||
| - | === Demonstration Articles === | ||
| - | |||
| - | ===== Theses (Abschlussarbeiten) ===== | ||
| - | |||
| - | === Master Theses === | ||
| - | |||
| - | === Bachelor Theses === | ||
| - | |||
| - | |||
| - | ===== Teaching ===== | ||
| - | |||
| - | ==== Fachprojekt (technical project) Digital Entertainment Technologies ==== | ||
| - | |||
| - | |||
| - | |||
| - | ==== Project Groups ==== | ||
| - | |||
| - | === PG 642: Verteiltes Deep Reinforcement Learning System zum Trainieren von Game AI === | ||
| - | |||
| - | The goal of this project group is to train agents to play Rocket League using a distributed Deep Reinforcement Learning system. | ||
| - | Training directly on Rocket League comes with many issues. Therefore, the game is reimplemented in Unity. | ||
| - | This raises the challenge of transferring the learned behavior in Unity to Rocket League, which is called a sim-to-sim transfer. | ||
| - | As this project is still ongoing, there are no outcomes to be presented yet. | ||
| - | |||
| - | |||
| - | |||
| - | |||
| - | |||
| - | ===== Links ===== | ||