Risk-sensitive MPCs with Deep Distributional Inverse RL for Autonomous Driving
Keuntaek Lee,David Isele,Evangelos A. Theodorou,Sangjae Bae,Keuntaek Lee,David Isele,Evangelos A. Theodorou,Sangjae Bae
In robot learning from demonstration (LfD), a visual representation of a cost function inferred from Inverse Reinforcement Learning (IRL) provides an intuitive tool for humans to quickly interpret the underlying objectives of the demonstration. The inferred cost function can be used by controllers, for example, Model Predictive Controllers (MPCs). In this work, we improve the recently developed IR...
