Practice Convergence And Complexity (9.3.3) - Reinforcement Learning and Bandits
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Convergence and Complexity

Practice - Convergence and Complexity

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Practice Questions

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Question 1 Easy

What does convergence mean in the context of dynamic programming?

💡 Hint: Think about the ultimate goal of an iterative process.

Question 2 Easy

What does time complexity measure?

💡 Hint: Focus on the resource that affects performance as input grows.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is convergence in dynamic programming?

A random process
Reaching an optimal solution
Time complexity measure

💡 Hint: Think about what the goal of iterative methods is.

Question 2

True or False: Space complexity measures the computational time required for an algorithm.

True
False

💡 Hint: Remember the difference between time and space.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a reinforcement learning scenario with a high-dimensional state space. Discuss the implications of using dynamic programming methods in this case and possible alternatives.

💡 Hint: Reflect on the scalability of algorithms in reinforcement learning.

Challenge 2 Hard

Create a small grid world environment. Implement both policy iteration and value iteration algorithms. Compare their performance in terms of convergence speed and computational efficiency.

💡 Hint: Consider running multiple trials to gather accurate performance data.

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Reference links

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