Scalable Multi-Task Imitation Learning with Autonomous Improvement

no code implementations • 25 Feb 2020 • Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn

In this work, we target this challenge, aiming to build an imitation learning system that can continuously improve through autonomous data collection, while simultaneously avoiding the explicit use of reinforcement learning, to maintain the stability, simplicity, and scalability of supervised imitation.

Imitation Learning reinforcement-learning +1