Design a computer system using tree search and reinforcement learning algorithms : Visualizing the Outcomes of the Epsil

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Information Technology (IT), Architecture, Social Studies
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University
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Hard
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5 questions
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1.
OPEN ENDED QUESTION
3 mins • 1 pt
What is the purpose of the epsilon greedy policy in Monte Carlo methods?
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2.
OPEN ENDED QUESTION
3 mins • 1 pt
Explain how the value function is generated from the state-action estimate.
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3.
OPEN ENDED QUESTION
3 mins • 1 pt
Describe the process of visualizing the outcomes of MC control.
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4.
OPEN ENDED QUESTION
3 mins • 1 pt
What role does the meshgrid function play in visualizing values in Monte Carlo methods?
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5.
OPEN ENDED QUESTION
3 mins • 1 pt
Summarize the key differences between Monte Carlo prediction and Monte Carlo control.
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