1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Extreme Event Prediction with Multi-agent Reinforcement Learning-based Parametrization of Atmospheric and Oceanic Turbulence
Rambod Mojgani, Daniel Waelchli, Yifei Guan +2
Global climate models (GCMs) are the main tools for understanding and predicting climate change. However, due to limited numerical resolutions, these models suffer from major struc…
cs.LG2023
Discovering Individual Rewards in Collective Behavior through Inverse Multi-Agent Reinforcement Learning
Daniel Waelchli, Pascal Weber, Petros Koumoutsakos
The discovery of individual objectives in collective behavior of complex dynamical systems such as fish schools and bacteria colonies is a long-standing challenge. Inverse reinforc…