As shown in Table 2, the linguistic output of SL & CL is closer to the language used by humans: Our agent is able to produce a much richer and less repetitive output than both BL and RL.
it learns to use a more diverse vocabulary, generates more unique questions, and repeats questions within the same dialogue at a much lower rate than the baseline and RL: 93.5% of the games played by BL contain at least one verbatim question repetition, for RL this happens in 96.47% of the cases, whereas for SL and CL this is for only 55.8% and 52.19% of the games, respectively.