This is a clever approach for solving a very old problem. And that problem is that random exploration really doesn't work for long time sequences: A while ago,

This is a clever approach for solving a very old problem. And that problem is that random exploration really doesn't work for long time sequences: A while ago, we participated in the Bomberland competition (won semi-finals, 2nd place overall) and we went with deep learning reinforcement learning and here's the rough math: It takes 1 step to place the bomb, 5 for the bomb to arm, 1 to detonate, 10 while there's fire. So you might not know until 17 steps later if placing that bomb was a good idea. You have 7 actions (up,down,left,right,bomb,detonate,nop) so the chance of getting that 17-step sequence correct by chance is (1/7)^17 = 4*10^-15. Or said the other way around, you need to let the AI try around 232,630,513,987,207 times to get it correct once. And that's why imitating someone else - no matter if they are an expert or not - will massively boost your learning performance. Because even the worst Mindcraft player on YouTube is still doing 1000x better than truly random exploration. (That said, we lost in the Bomberland finals against someone who analyzed the game theoretically and then just hard-coded the perfect strategy. Sometimes thinking hard is superior to all AI approaches...)