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GitHub / wanxinjin / Pontryagin-Differentiable-Programming
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.
Stars: 123
Forks: 16
Open Issues: 0
License: mit
Language: Python
Repo Size: 352 MB
Dependencies:
0
Created: over 4 years ago
Updated: 7 months ago
Last pushed: 7 months ago
Last synced: 7 months ago
Topics: control-learning, control-systems, differentiable-programming, dynamical-systems, end-to-end-learning, imitation-learning, inverse-reinforcement-learning, learning-control, motion-planning, optimal-control, pontryagin-maximum-principle, reinforcement-learning, reinforcement-learning-environments, system-identification, trajectory-optimisation, trajectory-optimization
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