Results of the DQN-based agent are presented in fig: scenario comparison. Each plot depicts the average reward (across 5 seeds) of all representations methods. It can be seen that the NLP representation outperforms the other methods.  NLP representations remain robust to changes in the environment as well as task-nuisances in the state.  
 Question: What result from experiments suggest that natural language based agents are more robust?
Average reward across 5 seeds show that NLP representations are robust to changes in the environment as well task-nuisances