Speaker
Brendan Tracey
(Google DeepMind)
Description
Reinforcement learning (RL) is a promising technology for the future of fusion power. A key challenge is to stabilize and regulate the plasma position and shape via magnetic fields generated by a set of control coils. This talk discusses our efforts to generate magnetic controllers using deep reinforcement learning. We train controllers on a Grad-Schafranov based simulator and then deploy the learned controller on experiments on the Tokamak à Configuration Variable (TCV). We show successful stabilization of a diverse set of plasma configurations, and discuss strategies to accelerate training time and improved performance.
| Speaker's Affiliation | Google DeepMind, London |
|---|---|
| Member State or IGO/NGO | United Kingdom |
Primary author
Brendan Tracey
(Google DeepMind)
