Divide & Conquer Imitation Learning
Alexandre Chenu,Nicolas Perrin-Gilbert,Olivier Sigaud,Alexandre Chenu,Nicolas Perrin-Gilbert,Olivier Sigaud
When cast into the Deep Reinforcement Learning framework, many robotics tasks require solving a long horizon and sparse reward problem, where learning algorithms struggle. In such context, Imitation Learning (IL) can be a powerful approach to bootstrap the learning process. However, most IL methods require several expert demonstrations which can be prohibitively difficult to acquire. Only a handfu...
