most citedInverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics

19 citations · 30 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2021★ 3 cited

Hierarchies of Planning and Reinforcement Learning for Robot Navigation

Jan Wöhlke, Felix Schmitt, Herke van Hoof

Solving robotic navigation tasks via reinforcement learning (RL) is challenging due to their sparse reward and long decision horizon nature. However, in many navigation tasks, high…

cs.LG2021

Reward (Mis)design for Autonomous Driving

W. Bradley Knox, Alessandro Allievi, Holger Banzhaf +2

This article considers the problem of diagnosing certain common errors in reward design. Its insights are also applicable to the design of cost functions and performance metrics mo…

eess.SY2016★ 1 cited

Exact Maximum Entropy Inverse Optimal Control for Modelling Human Attention Switching and Control

Felix Schmitt, Hans-Joachim Bieg, Dietrich Manstetten +2

Maximum Causal Entropy (MCE) Inverse Optimal Control (IOC) has become an effective tool for modelling human behaviour in many control tasks. Its advantage over classic techniques f…

eess.SY2016★ 7 cited

Predicting Lane Keeping Behavior of Visually Distracted Drivers Using Inverse Suboptimal Control

Felix Schmitt, Hans-Joachim Bieg, Dietrich Manstetten +2

Driver distraction strongly contributes to crash-risk. Therefore, assistance systems that warn the driver if her distraction poses a hazard to road safety, promise a great safety b…

cs.AI2016★ 19 cited

Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics

Michael Herman, Tobias Gindele, Jörg Wagner +2

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. Since the a…