Practice Thompson Sampling (9.8.3.4) - Reinforcement Learning and Bandits
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Thompson Sampling

Practice - Thompson Sampling - 9.8.3.4

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is Thompson Sampling primarily used for?

💡 Hint: Think about how it balances trying new options versus sticking to familiar ones.

Question 2 Easy

What does Bayesian approach help in Thompson Sampling?

💡 Hint: Consider how new data influences your conclusions.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does Thompson Sampling primarily address?

Exploration-Exploitation Dilemma
Data Collection Methods
Data Analysis Techniques

💡 Hint: Recall the challenges faced in reinforcement learning.

Question 2

True or False: In Thompson Sampling, the exploration of arms is purely random.

True
False

💡 Hint: Consider how actions are selected based on information rather than random chance.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

In a MAB scenario with three arms, describe how you would implement Thompson Sampling and evaluate its performance after 100 trials.

💡 Hint: Consider how to represent the prior and update based on results.

Challenge 2 Hard

Discuss the implications of using Thompson Sampling in a real-time application, such as web advertising. What challenges would you anticipate?

💡 Hint: Think about how the algorithm would respond to user interactions over time.

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Reference links

Supplementary resources to enhance your learning experience.