Tools
Learning to play Minecraft with Video PreTraining
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Brief
We trained a neural network to play Minecraft by Video PreTraining (VPT) on a massive unlabeled video dataset of human Minecraft play, while using only a small amount of labeled contractor data. With fine-tuning, our model can learn to craft diamond tools, a task that usually takes proficient humans over 20 minutes (24,000 actions). Our model uses the native human interface of keypresses and mouse movements, making it quite general, and represents a step towards general computer-using agents.
Why It Matters
Pendekatan ini menunjukkan arah baru bagi agen yang menggunakan antara muka manusia sambil mengurangkan kebergantungan pada data berlabel.