Reinforcement Learning and Deep RL Python Theory and Projects - Implementing Frozen Lake - 2

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5 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of setting a high number of episodes in reinforcement learning?
To increase the discount factor
To reduce the learning rate
To fill the Q-table with sufficient data
To ensure the agent explores all possible actions
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does the discount factor, gamma, influence in reinforcement learning?
The number of episodes
The speed of learning
The exploration rate
The importance of future rewards
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it important to set a maximum number of steps in each game?
To prevent the agent from getting stuck
To ensure the agent explores all actions
To decrease the discount factor
To increase the learning rate
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What role does epsilon play in the learning process of an agent?
It determines the learning rate
It sets the maximum number of episodes
It adjusts the discount factor
It controls the exploration-exploitation balance
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does the decay rate affect epsilon in reinforcement learning?
It increases epsilon over time
It keeps epsilon constant
It reduces epsilon gradually
It has no effect on epsilon
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