Before revision:  We evaluate MAGIC on several long-term planning tasks, showing that it significantly outperforms planning using primitive actions , hand-crafted macro-actions , as well as naive reinforcement learning in both simulation and on a real robot.
After revision:  We evaluate MAGIC on several long-term planning tasks, showing that it significantly outperforms planning using primitive actions and hand-crafted macro-actions , as well as naive reinforcement learning in both simulation and on a real robot.