Tokamak control by RL
Magnetic control of tokamak plasmas through deep reinforcement learning
Paper title Magnetic control of tokamak plasmas through deep reinforcement learning
Paper doi.org
A reinforcement-learning algorithm (MPO) trains a small neural network in a free-boundary plasma simulator to turn magnetic measurements and shape targets into voltage commands. The trained network then runs on the TCV tokamak with no further tuning and commands all 19 control coils at 10 kHz.
- Published
- Nature
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