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document
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Han, Minghao (author), Tian, Yuan (author), Zhang, Lixian (author), Wang, J. (author), Pan, W. (author)
Reinforcement learning (RL) is promising for complicated stochastic nonlinear control problems. Without using a mathematical model, an optimal controller can be learned from data evaluated by certain performance criteria through trial-and-error. However, the data-based learning approach is notorious for not guaranteeing stability, which is...
journal article 2021
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