A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
reinforcement-learning trajectory-optimisation motion-planning dynamical-systems control-systems trajectory-optimization optimal-control system-identification imitation-learning inverse-reinforcement-learning end-to-end-learning control-learning differentiable-programming reinforcement-learning-environments learning-control pontryagin-maximum-principle
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Updated
Oct 15, 2023 - Python