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