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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define what a value function is in reinforcement learning.
π‘ Hint: What does the agent aim to maximize?
Question 2
Easy
What is an episode?
π‘ Hint: Think of it as a complete journey in an environment.
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 is a value function in reinforcement learning?
π‘ Hint: Think about what the agent wants to achieve.
Question 2
In First-Visit Monte Carlo, how is the value of a state determined?
π‘ Hint: Focus on when the estimate is captured.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
You are given episodes from a simple grid world. Calculate the estimated value of specific states using both First-Visit and Every-Visit Monte Carlo methods.
π‘ Hint: Use the rewards from episodes fitting the definitions of each Monte Carlo method.
Question 2
Evaluate a scenario where the reward structure changes over time. How would First-Visit Monte Carlo differ from Every-Visit Monte Carlo in this context?
π‘ Hint: Consider how the timing of reward changes affects learning.
Challenge and get performance evaluation