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Machine learning control (MLC) is a subfield of machine learning, intelligent control, and control theory which aims to solve optimal control problems with machine learning methods. Key applications are complex nonlinear systems for which linear control theory methods are not applicable.
Applications, Types of problems and tasks & Adaptive Dynamic Programming
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control mlc learning nonlinear problems programming optimal systems methods dynamic applications known function adp theory regression also law example general
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| neural networks | instance of | in traditional dynamic programming by approximating value functions or control policies using parametric structures | 0.80 | text |
| Machine learning control | related to Adaptive Dynamic Programming | Adaptive Dynamic Programming | 0.60 | section |
| Machine learning control | related to Adaptive Dynamic Programming | ADP | 0.60 | section |
| Machine learning control | related to Adaptive Dynamic Programming | The | 0.60 | section |
| Machine learning control | related to Adaptive Dynamic Programming | Hamilton-Jacobi-Bellman | 0.60 | section |
| Machine learning control | related to Adaptive Dynamic Programming | HJB | 0.60 | section |
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