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I wonder if this is a tractable reinforcement learning problem. The objective is somewhat clearly defined-minimize spatial deviation over time from the input path.

In order to train the model, wouldn’t you want a physics simulation, so you can train the model quickly? But if you had a physics simulation, aren’t there much easier methods to use than machine learning?

Who said there was any machine learning?

The comment I was replying to was talking about machine learning.

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