4 papers · 1 filter
Inverse Dynamic Games Based on Maximum Entropy Inverse Reinforcement Learning
Jairo Inga, Esther Bischoff, Florian Köpf +1
We consider the inverse problem of dynamic games, where cost function parameters are sought which explain observed behavior of interacting players. Maximum entropy inverse reinforc…
Adaptive Dynamic Programming for Model-free Tracking of Trajectories with Time-varying Parameters
Florian Köpf, Simon Ramsteiner, Michael Flad +1
In order to autonomously learn to control unknown systems optimally w.r.t. an objective function, Adaptive Dynamic Programming (ADP) is well-suited to adapt controllers based on ex…
Partner Approximating Learners (PAL): Simulation-Accelerated Learning with Explicit Partner Modeling in Multi-Agent Domains
Florian Köpf, Alexander Nitsch, Michael Flad +1
Mixed cooperative-competitive control scenarios such as human-machine interaction with individual goals of the interacting partners are very challenging for reinforcement learning…
Adaptive Optimal Control for Reference Tracking Independent of Exo-System Dynamics
Florian Köpf, Johannes Westermann, Michael Flad +1
Model-free control based on the idea of Reinforcement Learning is a promising approach that has recently gained extensive attention. However, Reinforcement-Learning-based control m…