Practice Role Of Neural Networks In Rl (9.7.1) - Reinforcement Learning and Bandits
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Role of Neural Networks in RL

Practice - Role of Neural Networks in RL

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the role of neural networks in reinforcement learning?

💡 Hint: Think about how decisions are made in complex environments.

Question 2 Easy

Define Experience Replay.

💡 Hint: Consider how a player learns from past game moves.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a Q-value in reinforcement learning?

A function of state
A measure of reward
The expected reward for action

💡 Hint: Think about how rewards build up in a game.

Question 2

True or False: Experience Replay is used to update the neural network with only the most recent experience.

True
False

💡 Hint: Consider how learning from history can improve performance.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

How might you apply reinforcement learning to a game with both discrete and continuous actions? Describe an architecture and address potential challenges.

💡 Hint: Think about hybrid models that can handle varying action types.

Challenge 2 Hard

Analyze how prioritizing experience replay could enhance learning in a DQN. What are some potential drawbacks?

💡 Hint: Consider the balance between speed and accuracy in learning.

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Reference links

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