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RL summary
Udacity DRLND, Deep Reinforcement Learning for Continuous Control
DRLND Project 2: Continuous Control
Udacity DRLND REINFORCE
Udacity DRLND Project 3: The Tennis Environment
Stanford CS224R Deep Reinforcement Learning | Spring 2025 | Lecture 3: Policy Gradients
Why Does Policy Iteration Work
RL Context
Policy Iteration
Udacity DRLND Multi-agent Research paper presentation
Udacity Weekly Webinar DRLND - Continuous Control, Discretization , Deep RL and Taxi example
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Last Updated: September 28, 2026
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Summary
Twelth lecture video on the course "Reinforcement Learning" at Paderborn University during the summer term 2020. Source files ... In this project an agent is a two link arm wich end effector will be track an spherical volume in the space. REINFORCE with OpenAi Gym's Cartpole environment walkthrough. To learn more about enrolling in the graduate course, visit: ... In this Webinar we cover Continuous control, discretization, Deep Rl and go through the Tax example.