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Researchers develop provable imitation learning for plasma control in fusion

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a theoretical framework for imitation learning to control instabilities in partially-observed Vlasov--Poisson equations, a key challenge in nuclear fusion. The method distills expert policies, which use full phase-space data, into controllers that operate solely on macroscopic measurements. The study provides stability guarantees for the learned policies, with error floors dependent on the achievable behavior cloning loss under observation constraints. AI

IMPACT This research demonstrates the theoretical feasibility of using imitation learning for complex control problems in areas like nuclear fusion, potentially enabling more adaptive and stable systems.

RANK_REASON This is a theoretical research paper published on arXiv concerning a specific scientific problem.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Researchers develop provable imitation learning for plasma control in fusion

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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Xiaofan Xia, Qin Li, Wenlong Mou ·

    Provable imitation learning for control of instability in partially-observed Vlasov--Poisson equations

    arXiv:2605.05081v1 Announce Type: new Abstract: We consider the stabilization of Vlasov--Poisson plasma dynamics, a central control problem in nuclear fusion. Our focus is the gap between what an ideal controller would use and what experiments can actually observe: while optimal …

  2. arXiv cs.LG TIER_1 English(EN) · Wenlong Mou ·

    Provable imitation learning for control of instability in partially-observed Vlasov--Poisson equations

    We consider the stabilization of Vlasov--Poisson plasma dynamics, a central control problem in nuclear fusion. Our focus is the gap between what an ideal controller would use and what experiments can actually observe: while optimal policy may rely on the full phase-space state, p…

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