no code implementations • 15 Dec 2020 • Michael Herman, Jörg Wagner, Vishnu Prabhakaran, Nicolas Möser, Hanna Ziesche, Waleed Ahmed, Lutz Bürkle, Ernst Kloppenburg, Claudius Gläser
In this paper, we thoroughly analyze the requirements on pedestrian behavior prediction for automated driving via a system-level approach.
no code implementations • 19 Jun 2019 • Huang Xiao, Michael Herman, Joerg Wagner, Sebastian Ziesche, Jalal Etesami, Thai Hong Linh
Imitation Learning describes the problem of recovering an expert policy from demonstrations.
no code implementations • 15 May 2019 • Andrey Rudenko, Luigi Palmieri, Michael Herman, Kris M. Kitani, Dariu M. Gavrila, Kai O. Arras
With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important.
no code implementations • 9 Oct 2018 • Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke
Our filter module splits the filter task into multiple less complex and more interpretable subtasks.
no code implementations • 5 Oct 2018 • Jörg Wagner, Volker Fischer, Michael Herman, Sven Behnke
Generating a robust representation of the environment is a crucial ability of learning agents.
no code implementations • 13 Apr 2016 • Michael Herman, Tobias Gindele, Jörg Wagner, Felix Schmitt, Wolfram Burgard
Inverse Reinforcement Learning (IRL) describes the problem of learning an unknown reward function of a Markov Decision Process (MDP) from observed behavior of an agent.