Data Science Asked on April 24, 2021
I find these two concepts confusing because I feel that imitation learning is just a ‘subset’ of supervised learning. But after thinking hard enough, I could not think of any difference and feel that they are the same.
Are they the same? or different from each other?
In supervised learning each data example has a label.
Imitation learning is mapping from observations to actions and is generally considered part of reinforcement learning.
The primary difference between supervised learning and reinforcement learning are when the labels / rewards are available. Reinforcement learning labels / rewards are often time delayed. In supervised learning, the labels / rewards have to be available concurrently with all the data. In reinforcement learning, the agent might make several actions before receiving a reward.
Answered by Brian Spiering on April 24, 2021
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