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Michael Herman

Research Scientist

 Michael Hermann

About Me

I am a research scientist at the Bosch Center for Artificial Intelligence in the research group focusing on environmental understanding and decision making. I am currently working towards finalizing my PhD thesis about Inverse Reinforcement Learning under partially unknown transition models. My research is focused on learning appropriate environmental transition models to solve decision making problems. Furthermore, I am interested in reinforcement learning in uncertain environmental models as well as learning generalizable representations of an expert’s motivation or goal from observed behavior.

My research interests include: recurrent neural networks, Bayesian deep learning, reinforcement learning under uncertain transition models, and imitation learning.

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My Research Fields

  • Deep Learning
  • Reinforcement Learning
  • Inverse Reinforcement Learning