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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define stability in the context of deep reinforcement learning.
π‘ Hint: Think about how training can sometimes go wrong.
Question 2
Easy
What is exploration?
π‘ Hint: Consider how you might try new things in a game.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does stability refer to in deep reinforcement learning?
π‘ Hint: Think about how an algorithm should behave during training.
Question 2
True or False: Exploitation involves testing out new strategies.
π‘ Hint: Remember the definitions of exploration vs. exploitation.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Analyze a real-world scenario where low sample efficiency affects learning. How would you improve sample efficiency in that context?
π‘ Hint: Think about opportunities to leverage simulations.
Question 2
Propose a solution to stabilize training in a deep RL system that's experiencing oscillations. What adjustments can be made?
π‘ Hint: Consider methods that create a buffer between current and target learning.
Challenge and get performance evaluation