~

AAAI2021/paper.tex

@@ -186,12 +186,14 @@
   
   In this paper, \note{we are the first to successfully achieve high compositional
   symbolic language} in a \emph{natural} manner without handcrafted inductions.
-  Initially, by investigating the compositionality of emerged symbolic
+  Initially, by investigating the emerged symbolic
   language after removing the \emph{deliberately handcrafted}
-  inductions, we observe that the agent capacity plays a key role in
-  compositionality. We further reveal and characterize the \note{quantitative relationship}
+  inductions, we observe the difficulty in naturally generating high compositional
+  symbolic language.
+  %the agent capacity plays a key role in compositionality.
+  Further we reveal and characterize the \note{quantitative relationship}
   between the agent capacity and the compositionality of symbolic language, with
-  a novel mutual information-based metric for the compositionality. 
+  a novel mutual information-based metric for more reasonable measuring the compositionality. 
   % both theoretically and experimentally.
   %The theoretical analysis is built on the MSC
   %(Markov Series Channel) model for the language transmission process and a

AAAI2021/tex/introduction.tex

@@ -40,7 +40,9 @@ vocabulary can express infinite concepts.}
 \begin{figure}[t]
   \centering
   \includegraphics[width=0.99\columnwidth]{fig/Figure1_motivation.pdf}
-  \caption{}
+  \caption{The distribution of compositionality when training 50 times without
+    any induction. It can be observed that high compositional symbolic language
+    seldom emerged (e.g., 0 for compositionality $>0.99$).}
   \label{fig:induction}
   \end{figure}
 
@@ -49,8 +51,8 @@ through \emph{deliberately handcrafted} inductions, e.g., small vocabulary
 sizes~\cite{}, memoryless~\cite{}, carefully constructed rewards~\cite{}, and
 ease-of-teaching~\cite{}. \note{The possible intuition is that high compositional symbolic
 language cannot emerge without induction in existing multi-agent environment.}
-Figure~\ref{fig:induction} reports the compositionality when training two agents in the widely-used
-listener-speaker referential game, and it can be observed that \note{the compositionality
+Figure~\ref{fig:induction} reports the compositionality when training two agents
+in the widely-used listener-speaker referential game for 50 times, and it can be observed that \note{the compositionality
 of emerged symbolic language is extremely low without any induction}.
 Though such unnatural inductions are useful, they prevent us from better understanding the mystery of
 the emergence of language and even intelligence among our pre-human ancestors.
@@ -62,10 +64,10 @@ environment and agents are sufficient for achieving high compositionality.
 In this paper, we are the first work to achieve high compositional
 symbolic language without any deliberately handcrafted induction. The key observation
 is that the internal \emph{agent capacity} plays a crucial role in the
-compositionality of symbolic language,
-by %thoroughly
-analyzing the compositionality after removing the inductions in 
-the most widely-used listener-speaker referential game framework.
+compositionality of symbolic language.
+%by thoroughly
+%analyzing the compositionality after removing the inductions in 
+%the most widely-used listener-speaker referential game framework.
 Concretely, the relationship between the agent capacity and the compositionality 
 of symbolic language is characterized, with a novel mutual information-based
 metric for the compositionality.
@@ -180,12 +182,23 @@ In this paper, we made the following contributions:
 \item To our best knowledge, we are the first work to successfully achieve 
 high compositional symbolic
   language naturally, without any deliberately handcrafted induction.
-\item We thoroughly analyze the compositionality of emerged symbolic language
-  after removing deliberately handcrafted inductions, and confirm that the agent
-  capacity acts as a key factor for compositionality.
-\item We experimentally verified the conclusion for relationship between agent
+\item We analyze the compositionality of emerged symbolic language
+  after removing deliberately handcrafted inductions.
+\item We propose a novel mutual information-based metric to measure the
+  compositionality quantitatively, which is more reasonable.
+\item We experimentally exploited the relationship between agent
   capacity. Both theoretical analysis and
   experimental results lead to a counter-intuitive conclusion that lower agent
   capacity facilitates the emergence of symbolic language with higher
   compositionality.
 \end{itemize}
+
+
+The rest of this paper is arranged as follows.
+Section~\ref{sec:relatedwork} summarizes the related works.
+Section~\ref{sec:thory}
+introduces the experimental setup used in this study. Section~\ref{sec:mis}
+describes our proposed the novel mutual information-based metric for measuring
+the compositionality of symbolic language. Section~\ref{sec:exp} gives the
+experimental results of the exploration for the relationship between agent
+capacity and compositionality. Section~\ref{sec:con} concludes this paper.

AAAI2021/tex/last.tex

 \section{conclusion}
+\label{sec:con}
 
 In this paper, we are the first work to achieve high compositional
 symbolic language without any deliberately handcrafted induction.