RL4F provides the first standardized offline RL benchmark for multi-actuator long-horizon plasma control using DIII-D data, with model-based methods showing best average performance across rotation, density, temperature, and pressure tasks.
(2021).Development of free-boundary equilibrium and transport solvers for simulation and real-time interpretation of tokamak experiments
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Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark
RL4F provides the first standardized offline RL benchmark for multi-actuator long-horizon plasma control using DIII-D data, with model-based methods showing best average performance across rotation, density, temperature, and pressure tasks.