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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define exploration in the context of multi-armed bandits.
π‘ Hint: Relates to discovering new opportunities.
Question 2
Easy
What does exploitation refer to in reinforcement learning?
π‘ Hint: Think about sticking with what you know works.
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 the primary goal of exploration in multi-armed bandit problems?
π‘ Hint: Focus on the purpose of trying new things.
Question 2
True or False: Thompson Sampling always selects the action with the highest average reward.
π‘ Hint: Think about what probabilistic choices imply.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Design a multi-armed bandit algorithm using both Ξ΅-greedy and UCB strategies and explain the rationale behind each choice.
π‘ Hint: Consider how each strategy contributes to overall learning.
Question 2
Implement a Thompson Sampling algorithm for a simulated ad placement scenario, demonstrating how it adapts over time.
π‘ Hint: Focus on how probability distributions drive decision-making.
Challenge and get performance evaluation