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rudolph:cig_new [2021-10-27 15:35] Marco Pleines [Publications] |
rudolph:cig_new [2022-05-09 13:12] Marco Pleines [Theses (Abschlussarbeiten)] |
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| ===== Research Context ===== | ===== Research Context ===== | ||
| - | * Genetic and Evolutionary Algortihms | + | * Deep Reinforcement Learning |
| - | * Reinforcement Learning | + | |
| * Procedural Content Generation | * Procedural Content Generation | ||
| * Generative Models | * Generative Models | ||
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| ===== Publications ===== | ===== Publications ===== | ||
| + | === Conference Articles (peer reviewed) === | ||
| + | == 2020 == | ||
| - | === Journal Articles === | + | * 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 == | ||
| - | === Conference Articles (peer reviewed) === | + | * 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) ===== | ||
| + | |||
| + | Anybody who is interested in writing her or his thesis under the guidance of the above listed contacts has to submit a well written (not perfect) exposé. The exposé has to be made up of the following items: | ||
| + | |||
| + | * 2-3 DIN A4 pages | ||
| + | * Content | ||
| + | * Context of the thesis | ||
| + | * Goal and scope of the thesis | ||
| + | * Problems and challenges to be faced | ||
| + | * Relevance of conducting the thesis | ||
| + | * Initial approach | ||
| + | * Preliminary outline of the thesis | ||
| + | * Preliminary list of literature | ||
| + | |||
| + | Depending on the current interest rate, submitted exposés can be improved for a few iterations until it is good enough for the proposed thesis to be accepted and advised by us. __Note that we cannot guarantee a spot under our guidance beforehand__, because the demand of writing a thesis at our chair is usually much greater than our capacity. | ||
| + | |||
| + | === Bachelor Theses === | ||
| + | |||
| + | == 2022 == | ||
| + | |||
| + | * Leon Swazinna. Evaluation of the MA-POCA Algorithm in a Competitive Reinforcement Learning Environment.\\ Advisors: Rudolph, Pleines. | ||
| + | |||
| + | == 2021 == | ||
| + | |||
| + | * Alisa Gromova: Training Multiple Agents in a Soccer Environment using Deep Reinforcement Learning and Self-Play.\\ Advisors: Rudolph, Pleines. | ||
| + | * Markus Grigull: Sim-to-Real Transfer eines Reinforcement Learning Ansatzes zur mechanischen Steuerung eines Gamepads.\\ Advisors: Rudolph, Pleines. | ||
| == 2020 == | == 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. | + | * Matthias Pallasch. Curiosity-driven Exploration mit Reinforcement Learning in einer CoinRun Umwelt.\\ Advisors: Rudolph, Pleines. |
| + | * Vanessa Speeth. Entwicklung eines Agenten für das Spiel Azul basierend auf dem Advanced-Actor-Critc Ansatz.\\ Advisors: Rudolph, Pleines. | ||
| + | * Wentao Li. Applying Curriculum and Reinforcement Learning to a Marble Labyrinth Environment.\\ Advisors: Rudolph, Pleines. | ||
| + | == 2019 == | ||
| - | ===== Theses (Abschlussarbeiten) ===== | + | * Till Musshoff. Vergleich der Lersperformanz von Proximal Policy Optimization und Behavioral Cloning.\\ Advisors: Rudolph, Pleines. |
| + | * Marius Brinkmann. Evaluation der Reinforcement Learning-Algorithmen DQN und PPO in einer Ballwurf-Umwelt.\\ Advisors: Rudolph, Pleines. | ||
| === Master Theses === | === Master Theses === | ||
| - | === Bachelor Theses === | + | == 2022 == |
| + | |||
| + | * Marcel Schyma. Kontextunabhängige prozedurale Szenen- und Inhaltsgenerierung.\\ Advisors: Rudolph, Pleines. | ||
| + | |||
| + | == 2021 == | ||
| + | |||
| + | * Jonas Schumacher: Deep Reinforcement Learning für Stichspiele mit imperfekter Information / Deep Reinforcement Learning for Trick-Taking Games with Imperfect Information.\\ Advisors: Rudolph, Pleines. | ||
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| ==== Fachprojekt (technical project) Digital Entertainment Technologies ==== | ==== Fachprojekt (technical project) Digital Entertainment Technologies ==== | ||
| + | * [[https://ls11-www.cs.tu-dortmund.de/de/rudolph/lehre/fp_det_ws_21_22|WiSe 2021/2022]] | ||
| + | * Teacher: Patrick Dinklage | ||
| + | * [[https://ls11-www.cs.tu-dortmund.de/de/rudolph/lehre/fp_det_ss_21|SoSe 2021]] | ||
| + | * Teacher: Patrick Dinklage | ||
| + | * [[https://ls11-www.cs.tu-dortmund.de/de/rudolph/lehre/fp_det_ws20_21|WiSe 2020/2021]] | ||
| + | * Teacher: Marco Pleines | ||
| + | * [[https://ls11-www.cs.tu-dortmund.de/de/rudolph/lehre/fp_det_ss20|SoSe 2020]] | ||
| + | * Teacher: Marco Pleines | ||
| + | * [[https://ls11-www.cs.tu-dortmund.de/de/rudolph/lehre/fp_det_ws19_20|WiSe 2019/2020]] | ||
| + | * Teacher: Marco Pleines | ||
| + | * [[https://ls11-www.cs.tu-dortmund.de/de/rudolph/lehre/fp_det_ss19|SoSe 2019]] | ||
| + | * Teacher: Marco Pleines | ||
| ==== Project Groups ==== | ==== Project Groups ==== | ||
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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]] | ||
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| + | * [[https://github.com/LucasAlegre/sumo-rl|Traffic Control]] | ||
| + | |||
| + | * [[https://github.com/apigott/CityLearn|CityLearn]] | ||