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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is Dynamic Programming?
π‘ Hint: Think about how we tackle complicated tasks by breaking them down.
Question 2
Easy
Name a limitation of DP in reinforcement learning.
π‘ Hint: What happens to computations as we add more dimensions?
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 is the primary limitation of Dynamic Programming in large state spaces?
- Increased accuracy
- Computational infeasibility
- Simplified calculations
π‘ Hint: Consider how scalability affects computational methods.
Question 2
True or False: The curse of dimensionality means that adding dimensions simplifies the analysis of state spaces.
- True
- False
π‘ Hint: Think about what happens when we add more complexities.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a reinforcement learning problem with at least five states and analyze how DP would struggle in optimizing the policy as the state space increases.
π‘ Hint: Think about how many actions might be available in each state.
Question 2
Create a function approximation model that represents an MDP with ten states and compare its effectiveness to a DP approach.
π‘ Hint: How does function approximation mitigate memory issues?
Challenge and get performance evaluation