Commit 53ae178a by haoyifan

hao

parent 2800c9e4
......@@ -40,33 +40,18 @@ i.e., hidden layer size ($h_{size}$), from 6 to 100.
Figure~\ref{fig:exp1} reports the supplementally experimental results. Consistent with
previous experiments, it can be observed that the mean value of MIS decreases as the value
of $h_{size}$ increases, no matter what configuration we take.
Taking the
configuration of vocabulary size $|V|=10$ as an example, the mean value of MIS
is around 0.8 when $h_{size}\le 20$; MIS significantly decreases to 0.75 when
$h_{size}$ increases from 20 to 40; MIS further reduces to 0.7 when $h_{size}$
increases from 40 to 100.
For different vocabulary sizes, the MIS shares the
similar behavior.
It is because symbols in low-compositional languages carry semantic information
about more concepts. As a result, higher capacity is required to characterize the
complex semantic information for low-compositional language to emerge.
In summary, lower agent capacity improves the possibility of
emerging high compositional symbolic language.
\subsection{Ratio of high compositional language.}
We further breakdown our results to investigate the importance of agent capacity
to the compositionality of symbolic language. Figure~\ref{fig:exp2} reports the
ratio of high compositional symbolic language in all emerged languages,
Figure~\ref{fig:exp2} (a) and (b) for $\mathit{MIS}>0.99$ and $\mathit{MIS}>0.9$, respectively. It
can be observed that the ratio of high compositional symbolic languages
decreases drastically with the increase of $h_{size}$.
Taking vocabulary size $|V|=4$ as an example, symbolic languages with
compositionality $\mathit{MIS}>0.99$ take $>$10\% mainly over all the emerged symbolic
languages, when $h_{size}<20$; the ratio reduces to 0\%$\sim$5\% when $h_{size}$
increases to 40; the ratio reduces around 3\% when $h_{size}$ goes beyond 40.
$\mathit{MIS}>0.9$ reports similar results.
of $h_{size}$ increases, no matter what configuration we take. MIS significantly decreases
from around 0.8 to less than 0.7 when $h_{size}$ increases from 6 to 100.
Just like we do in the \emph{Experiment} section, we further breakdown our results to show the importance
of agent capacity for emerging a symbolic language with high compositionality. Figure~\ref{fig:exp2} reports
the ratio of high compositional symbolic language in all emerged languages,
Figure~\ref{fig:exp2} (a) and (b) for $\mathit{MIS}>0.99$ and $\mathit{MIS}>0.9$, respectively.
Under these two supplementary configuration, we also find that the ratio of high compositional symbolic languages
decreases drastically with the increase of $h_{size}$, and such ratio would be closed to zero when agent capacity
comes too large (i.e., $h_{size} > 80$).
Notably, when $h_{size}$ is large enough (e.g., $>40$), high compositional
symbolic language is hard to emerge in a natural referential game, for
easy-to-emerge low compositional symbolic language is sufficient in scenarios of
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