In Reinforcement Learning, when I train a model, it comes up with its own set of solutions. For example, if I am training a robot to walk, it will come up with its own walking gait, such as this Deep Mind robot that has learned to walk in a bizarre gait. It can surely walk/run although the movements does not quite look like a human.
I was wondering how can I train a model by providing it some kind of reference motion data? For example, if I collect motion data from a walking human and then provide it to the training, can the training be made learn the walking movements that looks similar to the reference motion data?
Searching online I did find some links that shows this is possible. For example, here is a research where the researchers did exactly what I am trying to do, they fed motion data captured from humans to a simulation and made it learn the movements.
So, my question is: How can I give some kind of hints or reference data to a reinforcement learning model instead of just leaving it all by itself? how exactly is this done? What is it even called? What are some terms and keywords that I can search for to learn more?
Many thanks in advance