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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is Q-Learning?
💡 Hint: It's a value-based method.
Question 2
Easy
What is the purpose of DQNs?
💡 Hint: Think of environments with many possible states.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does Q-Learning focus on?
- Maximizing exploration
- Learning value of actions
- Directly learning policies
💡 Hint: It's a foundational value-based technique.
Question 2
True or False: DQNs can handle large state spaces efficiently.
- True
- False
💡 Hint: Think about how the complexity of states is managed.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a simple agent using Q-Learning for a grid-based game where the goal is to reach the top-right corner. Outline the Q-table structure and the expected updates.
💡 Hint: Consider how rewards would be assigned in this environment.
Question 2
Compare the effectiveness of DQNs versus classical Q-Learning in a scenario involving high-dimensional sensor data, such as in robotics.
💡 Hint: Think about the capabilities of neural networks in processing complex data.
Challenge and get performance evaluation