Practice Reinforcement Learning (10) - Reinforcement Learning

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9 questions

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

Question 1.
Define reinforcement learning in your own words.
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Consider how we learn from feedback.
Question 2.
What is a reward in reinforcement learning?
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Think of it as a 'score' for actions.
3Question 3.
What is the primary goal of reinforcement learning?
- To minimize errors
- To maximize cumulative rewards
- To classify data
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Think about what agents are trying to achieve.
4Question 4.
True or False: A stochastic policy guarantees the same action every time from a given state.
- True
- False
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Remember how randomness plays a role.
Question 5.
Consider a robot learning to walk in a simulated environment. How would you design the reward system to ensure it learns effectively?
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Think of how positive and negative feedback influences learning.
Question 6.
You are tasked with developing a deep Q-network for a video game AI. Discuss potential challenges and solutions in training such a network.
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Consider how real-world implementation differs from theoretical models.

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