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like I said above, we certainly hope so! It has been slow progress so far but applying modern ML / control techniques to tokamaks is one of the truly exciting applications of the current generation of AI in my opinion. Biased because this is literally what I do all day


Do you have a website or any papers on your work I could read?


I need to redo my website, just getting into the more public part of my PhD. Papers I would recommend from our collaboration on

control of normalized plasma pressure: https://papers.nips.cc/paper/2019/hash/7876acb66640bad41f1e1...

plasma profile transport modeling: https://iopscience.iop.org/article/10.1088/1741-4326/abe08d/...

hybrid dynamical modeling of gross plasma quantities: https://arxiv.org/abs/2006.12682

uncertainty quantification for plasma dynamics: https://arxiv.org/abs/2011.09588

It's still early days for this work and for us but we're looking at pushing reinforcement learning in methods and engineering to solve this problem


Do you have a github repo for the controller software? It will be fiberop to the sensors? And currentcontrolling by the ai?

Have you considered antagonistic training? One AI tries to destabilize the proces, the other trains not against a simulation, but against the destabilizing input and a succes-metric?




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