
Controlling Fusion Reactor Instability with Deep Reinforcement Learning with Aza Jalalvand - #682
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Harnessing AI for Plasma Stability
This chapter explores the use of reinforcement learning to address tearing mode instability in fusion reactors, focusing on targeted solutions over broad approaches. It also discusses the development of a neural network-based simulator and the challenges of applying traditional control methods, drawing parallels to pilot training for effective reactor management.
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