Before revision:  We evaluate MAGIC on several long-term planning tasks , showing that it significantly outperforms planning using primitive actions and hand-crafted macro-actions 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 in both simulation and on a real robot . The experimental results show that the learned macro-actions offer significant benefits in online planning performance, compared with primitive actions and handcrafted macro-actions .