Lecture 28 - Optimization and Learning for Robot Control - Summary and Conclusions

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Lecture 27 - Optimization and Learning for Robot Control - Policy Gradient Methods

Lecture 22 - Optimization and Learning for Robot Control - SARSA, Q-Learning

Lecture 25 - Optimization and Learning for Robot Control - Value function approximation

Lecture 26 - Optimization and Learning for Robot Control - Training a neural network with PyTorch

Lecture 24 - Optimization and Learning for Robot Control - Implementing SARSA and Q-Learning

Lecture 23 - Optimization and Learning for Robot Control - Implementing Monte Carlo and TD learning

Lecture 21 - Optimization and Learning for Robot Control - Temporal Difference Learning

RI Seminar: Nikolay Atanasov : Learning Environment Models for Mobile Robot Autonomy