Practice - Convergence and Complexity
Practice Questions
Test your understanding with targeted questions
What does convergence mean in the context of dynamic programming?
💡 Hint: Think about the ultimate goal of an iterative process.
What does time complexity measure?
💡 Hint: Focus on the resource that affects performance as input grows.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is convergence in dynamic programming?
💡 Hint: Think about what the goal of iterative methods is.
True or False: Space complexity measures the computational time required for an algorithm.
💡 Hint: Remember the difference between time and space.
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Challenge Problems
Push your limits with advanced challenges
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.
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
Supplementary resources to enhance your learning experience.