Master Thesis in Multi Agent System Reinforcement Learning

Job description

Safe Intelligence — this forms the core brand of the Fraunhofer Institute for Cognitive Systems IKS . Connected cognitive systems drive innovation in many sectors, including mobility, healthcare, and automation in industry. Disruptive technologies such as artificial intelligence and quantum computing play a key role here. Fraunhofer IKS is conducting research to ensure that these applications are reliable and verifiably safe. We consider resilience and intelligence to be part of the same process.: Be part of change We invite motivated master’s students to contribute to our leading-edge research by writing their thesis under our supervision. This project builds upon our prior work in Multi Agent Reinforcement Learning (MARL) for real-world use-case of aerial ad hoc networks (see our paper ) and aims to advance the solution by integrating state-of-the-art MARL methods, with a strong emphasis on scalability and reliability. What you contribute What you contribute: - Experience with Python ML stack, e.g. TensorFlow, Stable-Baselines3 - Strong background in Reinforcement Learning - Familiarity with Multi Agent Systems and / or Game Theory - Familiarity with working with Linux OS and git...