Practice Upper Confidence Bound (UCB) - 9.8.3.3 | 9. Reinforcement Learning and Bandits | Advance Machine Learning
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβ€”perfect for learners of all ages.

games

9.8.3.3 - Upper Confidence Bound (UCB)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does UCB stand for?

πŸ’‘ Hint: Think about the balance between exploration and rewards.

Question 2

Easy

Why is it important to factor in uncertainty in the UCB strategy?

πŸ’‘ Hint: Consider what happens when we only stick with known rewards.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does UCB primarily help with in multi-armed bandit problems?

  • Maximizes profit
  • Balances exploration and exploitation
  • Minimizes costs

πŸ’‘ Hint: Consider why strategies are needed when facing uncertain outcomes.

Question 2

True or False: UCB encourages exploration based on the confidence of action estimates.

  • True
  • False

πŸ’‘ Hint: Think about how uncertainty influences decision-making.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a simple algorithm using the UCB methodology for selecting which products to recommend in an e-commerce platform. Describe key challenges.

πŸ’‘ Hint: Reflect on how to proportionally adjust the selection based on feedback.

Question 2

Consider a scenario where multiple applications of UCB could lead to conflicting recommendations. How would you resolve these discrepancies in a real system?

πŸ’‘ Hint: Think about using consensus or averages from multiple sources to balance decisions.

Challenge and get performance evaluation