Magnetic control of tokamak plasmas through deep reinforcement learning
Jonas Degrave(Google DeepMind (United Kingdom)), Martin Riedmiller(California Institute of Technology), Abbas Abdolmaleki(Google DeepMind (United Kingdom)), F. Carpanese(Google DeepMind (United Kingdom)), S. Coda(École Polytechnique Fédérale de Lausanne), Pushmeet Kohli(Google DeepMind (United Kingdom)), Roland Hafner(Google DeepMind (United Kingdom)), Timo Ewalds(Google DeepMind (United Kingdom)), David Pfau(Google DeepMind (United Kingdom)), C. Sommariva(École Polytechnique Fédérale de Lausanne), A. Fasoli(École Polytechnique Fédérale de Lausanne), A. Merle(École Polytechnique Fédérale de Lausanne), O. Sauter(École Polytechnique Fédérale de Lausanne), Seb Noury(Google DeepMind (United Kingdom)), Maria Tsimpoukelli(Google DeepMind (United Kingdom)), Jackie Kay(Google DeepMind (United Kingdom)), Brendan Tracey(Google DeepMind (United Kingdom)), Michael Neunert(Google DeepMind (United Kingdom)), B.P. Duval(École Polytechnique Fédérale de Lausanne), Craig Donner(Google DeepMind (United Kingdom)), Diego de Las Casas(Google DeepMind (United Kingdom)), Jonas Buchli(Google DeepMind (United Kingdom)), James Keeling(Google DeepMind (United Kingdom)), F. Felici(École Polytechnique Fédérale de Lausanne), Federico Pesamosca, Leslie Fritz(Google DeepMind (United Kingdom)), Koray Kavukcuoglu(Google DeepMind (United Kingdom)), Andrea Huber(Google DeepMind (United Kingdom)), Demis Hassabis(Google DeepMind (United Kingdom)), J.M. Moret(École Polytechnique Fédérale de Lausanne), C. Galperti(École Polytechnique Fédérale de Lausanne)
Cited by 698
Related Papers
Human-level control through deep reinforcement learning
|Nature|2015|29.9k
AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models
|Nucleic Acids Research|2021|8.2k
Playing Atari with Deep Reinforcement Learning
|arXiv (Cornell University)|2013|5.1k
A direct adaptive method for faster backpropagation learning: the RPROP algorithm
|IEEE International Conference on Neural Networks|2002|3.9k