Practice Rewards (10.2.1) - Reinforcement Learning - AI Course Fundamental

Practice: Rewards

Lesson 10.2.1Reinforcement Learning

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9 questions

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3 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is a reward in the context of reinforcement learning?
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Think about how an agent is guided towards better actions.
Question 2.
Why does an agent want to maximize rewards?
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Consider what it means to perform well in a task.
3Question 3.
What is the main purpose of a reward in reinforcement learning?
- To punish the agent for mistakes
- To guide the agent towards desirable behavior
- To confuse the agent
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Think about how you are rewarded in games.
4Question 4.
True or False: An agent always focuses on obtaining future rewards over present ones.
- True
- False
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Consider how instant gratification might alter decisions.
Question 5.
Design a scenario where an agent must choose between a smaller immediate reward and a promise of a larger future reward. Explain how it should make its decision.
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Consider how waiting for something better might feel.
Question 6.
Critically analyze the impact of negative rewards (penalties) on learning efficiency. Provide a real-world example.
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Think about how feedback, both good and bad, influences behavior.

5 more questions in this section. Enroll free to practise them all.