Meta-learning framework adapting iMAML for rapid controller tuning on uncertain nonlinear systems via offline source data and limited online target adaptation, shown with neural state-space and DQN variants.
Meta-learning linear quadratic regulators: A policy gradient maml approach for the model- free LQR,
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Meta-Learning for Rapid Adaptation in Reference Tracking of Uncertain Nonlinear Systems
Meta-learning framework adapting iMAML for rapid controller tuning on uncertain nonlinear systems via offline source data and limited online target adaptation, shown with neural state-space and DQN variants.