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What is the role of 'reward' in reinforcement learning?
What is the role of 'reward' in reinforcement learning?
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Practice Questions
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Q1
What is the role of 'reward' in reinforcement learning?
To measure the accuracy of predictions
To provide feedback to the agent about its actions
To cluster data points
To evaluate the model's performance
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The reward provides feedback to the agent about the effectiveness of its actions, guiding it towards optimal behavior.
Questions & Step-by-step Solutions
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Q
Q: What is the role of 'reward' in reinforcement learning?
Solution:
The reward provides feedback to the agent about the effectiveness of its actions, guiding it towards optimal behavior.
Steps: 6
Show Steps
Step 1: Understand that reinforcement learning involves an agent that makes decisions.
Step 2: Know that the agent takes actions in an environment.
Step 3: Realize that after each action, the agent receives a reward.
Step 4: Understand that the reward is a signal that tells the agent how good or bad its action was.
Step 5: Learn that the agent uses this feedback to improve its future actions.
Step 6: Recognize that the goal of the agent is to maximize the total reward over time.
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