- Global Rewards in Hybrid Multi-Agent Deep Reinforcement Learning for Autonomous Mobility-on-Demand Systems. (Talk / OR 2024 Conference, Munich) 2024 more…
- Global rewards in multi-agent deep reinforcement learning for autonomous mobility on demand systems. 6th Annual Learning for Dynamics & Control Conference, 2024University of Oxford more…
- Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems. 2023, more…
Heiko Hoppe
Contact
Arcisstraße 21, 80333 Munich, Germany
Building 505, Room 1545
E-Mail: heiko.hoppe@tum.de
Short Biography
Heiko is a PhD student at the Chair of Business Analytics & Intelligent Systems at the TUM School of Management and a PhD Fellow at the Munich Data Science Institute. Heiko holds a Bachelor’s degree in Management and Technology and a Master’s degree in Finance and Information Management (FIM) from TUM. Before his PhD, Heiko conducted research at TUM and at Polytechnique Montréal, Canada. His research focuses on developing scalable Deep Reinforcement Learning algorithms for industrial applications, particularly on handling very large and interdependent action spaces in Reinforcement Learning.
Outside of academia, Heiko enjoys rowing, hiking, history, and reading.
Research Interests
- Deep Reinforcement Learning
- Scalable AI
- Industrial applications of AI: vehicle dispatching, inventory control, production scheduling