Practice Actor-critic A2c, Ppo, Ddpg (3.4) - Reinforcement Learning and Decision Making

Practice: Actor-Critic A2C, PPO, DDPG

Lesson 3.4Reinforcement Learning and Decision Making

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10 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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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does the Actor component do in Actor-Critic methods?
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Think about who makes choices.
Question 2.
What is the function of the Critic?
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Consider who gives feedback.
3Question 3.
What does 'Actor' refer to in Actor-Critic methods?
- Evaluates actions
- Selects actions
- None of the above
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Consider who makes decisions.
4Question 4.
Is the Critic's role to provide value evaluations?
- True
- False
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What does the Critic do in the Actor-Critic pairing?
Question 5.
Design a hybrid algorithm incorporating features from A2C, PPO, and DDPG to address a reinforcement learning problem of your choice. Discuss potential benefits and drawbacks.
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Think about the unique strengths of each algorithm.
Question 6.
Analyze a scenario where unstable updates could severely impact the agent's performance. What strategies could be implemented to mitigate these issues using concepts from the A2C and PPO algorithms?
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Consider the structural features of these algorithms.

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