Lecture
Elements of Reinforcement Learning
Description
This lecture covers the fundamental elements of Reinforcement Learning, including discrete states, actions, and rewards. It explains the concept of states transitioning based on actions taken, and how rewards are associated with these transitions. The lecture also presents a practical example with the Acrobot system, illustrating the application of Reinforcement Learning in a real-world scenario.
Official source
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