One-Shot Imitation Learning. Yan Duan et al. 2017

Summary Abstract Ideally, robots should be able to learn from very few demonstrations of any given task, and instantly generalize to new situations of the same task, without requiring task-specific engineering. In this paper, we propose a meta-learning framework for achieving such capability, which we call one-shot imitation learning. Task examples: to stack all blocks […]