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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does TD Learning enable agents to do?
π‘ Hint: Think about how agents adapt in real-time.
Question 2
Easy
What is the main characteristic of TD(0)?
π‘ Hint: Consider how it processes rewards.
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 does TD Learning primarily aim to do?
π‘ Hint: Think about how learning occurs in real-time.
Question 2
Is TD(0) a form of Monte Carlo method?
π‘ Hint: Remember the characteristics of both methods.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Design a simple TD Learning algorithm for a grid world where the agent receives rewards based on reaching specific destinations.
π‘ Hint: Consider how the agent will experience different rewards as it navigates the grid.
Question 2
Critique the use of SARSA vs. Q-learning in a dynamic changing environment.
π‘ Hint: Think about adaptability vs. exploration efficiency.
Challenge and get performance evaluation