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What is the difference between 'on-policy' and 'off-policy' learning?

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Question: What is the difference between \'on-policy\' and \'off-policy\' learning?

Options:

  1. On-policy learns from the current policy, off-policy learns from a different policy
  2. On-policy uses supervised learning, off-policy uses unsupervised learning
  3. On-policy is faster than off-policy
  4. There is no difference

Correct Answer: On-policy learns from the current policy, off-policy learns from a different policy

Solution:

On-policy learning updates the policy based on actions taken by the current policy, while off-policy learning can learn from actions taken by a different policy.

What is the difference between 'on-policy' and 'off-policy' learning?

Practice Questions

Q1
What is the difference between 'on-policy' and 'off-policy' learning?
  1. On-policy learns from the current policy, off-policy learns from a different policy
  2. On-policy uses supervised learning, off-policy uses unsupervised learning
  3. On-policy is faster than off-policy
  4. There is no difference

Questions & Step-by-Step Solutions

What is the difference between 'on-policy' and 'off-policy' learning?
  • Step 1: Understand that 'policy' means a strategy or a set of rules that decides what actions to take in a situation.
  • Step 2: In 'on-policy' learning, the learning process uses the actions taken by the current policy to improve itself.
  • Step 3: In 'off-policy' learning, the learning process can use actions taken by a different policy, not just the current one.
  • Step 4: Think of 'on-policy' as learning from your own experiences, while 'off-policy' is like learning from someone else's experiences.
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