382 citations · 801 across the 48 of their papers we have counts for
4 papers · 1 filter
An Algorithmic Perspective on Imitation Learning
Takayuki Osa, Joni Pajarinen, Gerhard Neumann +3
As robots and other intelligent agents move from simple environments and problems to more complex, unstructured settings, manually programming their behavior has become increasingl…
Towards Fine Grained Network Flow Prediction
Patrick Jahnke, Emmanuel Stapf, Jonas Mieseler +2
One main challenge for the design of networks is that traffic load is not generally known in advance. This makes it hard to adequately devote resources such as to best prevent or m…
Adaptation and Robust Learning of Probabilistic Movement Primitives
Sebastian Gomez-Gonzalez, Gerhard Neumann, Bernhard Schölkopf +1
Probabilistic representations of movement primitives open important new possibilities for machine learning in robotics. These representations are able to capture the variability of…
Deep Reinforcement Learning for Swarm Systems
Maximilian Hüttenrauch, Adrian Šošić, Gerhard Neumann
Recently, deep reinforcement learning (RL) methods have been applied successfully to multi-agent scenarios. Typically, these methods rely on a concatenation of agent states to repr…