Practice Exploration Vs. Exploitation (6.2) - Reinforcement Learning and Decision Making

Practice: Exploration vs. Exploitation

Lesson 6.2Reinforcement Learning and Decision Making

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9 questions

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4 cards from this section. Quick, good the night before a test.
Exercise
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Quiz
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6 sample questions

Question 1.
Define exploration in the context of reinforcement learning.
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Think about what it means to try new options.
Question 2.
What is exploitation in reinforcement learning?
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Consider how one might focus on already successful strategies.
3Question 3.
What does exploration in reinforcement learning involve?
- Ignoring new actions
- Trying new actions
- Only using known actions
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It’s about experimenting rather than sticking to what you know.
4Question 4.
True or False: Exploitation is more important than exploration in all cases of reinforcement learning.
- True
- False
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Consider situations that necessitate discovering new actions.
Question 5.
Propose a reinforcement learning model that optimally balances exploration and exploitation in a multi-armed bandit problem.
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Consider how an agent can gather enough data to make informed choices while still seeking new rewarding actions.
Question 6.
Develop an exploration-exploitation strategy for an artificial agent tasked with playing a game against human opponents.
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Think about how this agent can profile human players while still allowing for unpredictable, exploratory behavior.

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