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CI in Games
Solving Problems in Games
by Means of
Computational Intelligence
Research Context
- Genetic and Evolutionary Algortihms
- Reinforcement Learning
- Procedural Content Generation
- Generative Models
- Deep Learning
Contacts
Games for Computational Intelligence Research
Publications
Journal Articles
Conference Articles (peer reviewed)
Technical Reports
Demonstration Articles
Theses
Master Theses
Bachelor Theses
Teaching
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.