This bachelor thesis was written during my bachelor for computer science at the Karlsruher Institut for Technology (KIT). It was created with the help of the Autonomous Learning Robots (ALR) Lab of the KIT.
This paper tries to combine multi-agent reinforcement learning (MARL) with graph neural networks (GNNs). For the scope of a bachelor thesis we tried to improve upon the concepts found in Ruede et al. which was developed at the ALR Lab previously. We applied multi-hop message-passing GNNs to model inter-agent communication.
The thesis template was provided by the ALR. The main content of the thesis is provided in the main folder. It uses LaTeX.
The compiled thesis can be found in the main folder under thesis.pdf.
The machine learning source code of the bachelor thesis used an internal library of the ALR Lab, which hasn't been published yet. Therefore my contributions cannot be made public at this date.