Maximilian Hüttenrauch
After taking machine learning classes during his studies of electrical engineering, Max decided to pursue a Ph.D. in computer science with a focus on reinforcement learning, which he is currently finishing. During his Ph.D., he mainly worked on deep reinforcement learning for decentralized swarm control and black-box optimization for movement primitives in robotic manipulation. Starting in 2023, he continues working on reinforcement related topics as an AI Researcher at appliedAI.

Max's work

Seminar

Episode-based RL with Movement Primitive

Maximilian Hüttenrauch, AI Researcher at appliedAI Institute, talks about episode-based reinforcement learning with movement primitive.

Maximilian Hüttenrauch
Reinforcement Learning
Software

Tianshou: An elegant deep reinforcement learning library

Tianshou is a deep reinforcement learning library based on pure PyTorch. It caters to the needs of researchers and practitioners alike by …

Michael Panchenko Dominik Jain Maximilian Hüttenrauch
Reinforcement Learning