Reinforcement Learning and Deep RL Python Theory and Projects - Epsilon

The video tutorial introduces the concept of epsilon and its significance in decision-making between exploration and exploitation. It explains how epsilon influences the choice to explore new actions or exploit known information, particularly in the context of a Q-table. The tutorial also covers the implementation of epsilon in code, demonstrating the use of a random uniform function to determine actions. Finally, it discusses the importance of updating the epsilon value over time to balance exploration and exploitation effectively.

Describe a scenario where you would choose to exploit rather than explore.

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What happens when the random uniform value is less than the epsilon value?

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Why is it important to update the epsilon value in the code?

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