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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does ε represent in the ε-greedy strategy?
💡 Hint: Think about how often the agent randomizes its action.
Question 2
Easy
What is the main advantage of the ε-greedy strategy?
💡 Hint: Consider the implications of trying new options.
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 the ε in ε-greedy represent?
💡 Hint: What percentage is usually used for exploration?
Question 2
True or False: The softmax strategy always chooses the highest expected reward action.
💡 Hint: Is it a fixed choice every time?
Solve and get performance evaluation
Push your limits with challenges.
Question 1
In a scenario with three arms of a bandit, with expected rewards of [1, 2, 4] and ε = 0.2, calculate the probability of selecting each action using ε-greedy.
💡 Hint: Divide ε properly among the arms.
Question 2
Given the following expected rewards for four actions: [3, 4, 7, 8], compute their softmax probabilities with τ=1.
💡 Hint: Be careful with your calculations while applying softmax.
Challenge and get performance evaluation