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rudolph:cig_new [2020-06-25 19:47]
Marco Pleines [Games for Computational Intelligence Research]
rudolph:cig_new [2022-05-09 13:12] (current)
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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   * [[staff:​rudolph|Prof. Dr. Günter Rudolph]]   * [[staff:​rudolph|Prof. Dr. Günter Rudolph]]
   * [[staff:​pleines|Marco Pleines]]   * [[staff:​pleines|Marco Pleines]]
 +  * [[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) ===== 
 + 
 +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 == 
 + 
 +  * 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 == 
 + 
 +  * 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 === 
 + 
 +== 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. 
 + 
 + 
 + 
 +===== Teaching ===== 
 + 
 +==== 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 ==== 
 + 
 +=== 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://​github.com/​Nordeus/​heroic-rl|Heroic Magic Duel]]   * [[https://​github.com/​Nordeus/​heroic-rl|Heroic Magic Duel]]
-===== Publications ===== 
  
-=== Journal Articles === +  * [[https://​github.com/​MiscellaneousStuff/​pylol|League of Legends]]
-  +
-=== Conference Articles (peer reviewed) ===+
  
-=== Technical Reports ===+  * [[https://​pypi.org/​project/​catanatron/​|Catan]]
  
-=== Demonstration Articles ===+  * [[https://​sites.google.com/​view/​arena-unity/​home/​learning-environments|Arena]]
  
-===== Teaching ===== +  * [[https://​github.com/​LucasAlegre/​sumo-rl|Traffic Control]]
- +
-=== Completed Project Groups === +
- +
-=== Current Project Group === +
- +
-=== Current Diploma Theses === +
- +
- +
-=== Completed Diploma Theses === +
- +
- +
-=== Current Master Theses ===+
  
-=== Completed Master Theses === +  * [[https://​github.com/​apigott/​CityLearn|CityLearn]]
- +
-=== Current Bachelor Theses ===   +
- +
-=== Completed Bachelor Theses ===  +
- +
-=== Completed Seminar === +
- +
-===== Project Groups ===== +
- +
-=== PG 511 === +
- +
-=== PG 529 === +
- +
-== Stragotiator == +
- +
-===== Fachprojekte (technical projects) Digital Entertainment Technologies ===== +
- +
-===== Links =====+
  
 
Last modified: 2022-05-09 13:12 by Marco Pleines
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