haoyifan update intro

AAAI2021/tex/introduction.tex

@@ -40,9 +40,9 @@ vocabulary can express almost infinite concepts.}
 \begin{figure}[t]
   \centering
   \includegraphics[width=\columnwidth]{fig/Figure1_motivation.pdf}
-  \caption{The distribution of compositionality for 100 emerged symbolic
+  \caption{The distribution of compositionality for 100 emergent
     languages without
-    any induction. It can be observed that high compositional symbolic language
+    any induction. It can be observed that high compositional language
     seldom emerged (e.g., $<5\%$ for compositionality $>0.99$). Moreover, varying
     the vocabulary size does not affect the compositionality notably.}
   \label{fig:induction}
@@ -71,11 +71,11 @@ vocabulary can express almost infinite concepts.}
     \end{tabular}
   \end{table*}
 
-Prior studies focus on achieving high compositional symbolic language
+Prior studies focus on achieving high compositional language
 through \emph{deliberately handcrafted} inductions, e.g., additional rewards~\cite{},
 constructed loss functions~\cite{}, structural input data~\cite{},
 memoryless~\cite{}, and ease-of-teaching~\cite{}.
-\note{Such optimization methodologies are driven by the challenges to generate high compositional symbolic without induction in an existing multi-agent environment.}
+\note{Such optimization methodologies are driven by the challenges to generate high compositional language without induction in an existing multi-agent environment.}
 
 Figure~\ref{fig:induction} reports the compositionality when training two agents
 in the widely-used listener-speaker referential game~\cite{} for emerging 100
@@ -85,7 +85,7 @@ without any induction. Moreover, varying
 the vocabulary size does not affect the compositionality notably.}
 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.
-Yet, few works investigate the emergence of high compositional symbolic language
+Yet, few works investigate the emergence of high compositional language
 \emph{naturally}, i.e., without handcrafted inductions.
 In other words, it is never clear whether \emph{natural}
 environment and agents are sufficient for achieving high compositionality.
@@ -108,8 +108,8 @@ Regarding the theoretical analysis, we propose
 a novel mutual information-based metric to measure the compositionality quantitatively.
 %experimentally
 Regarding the experimental validation, we exploit the relationship between agent
-capacity and the compositionality of symbolic language that emerged
-\emph{naturally} in our experiments.
+capacity and the compositionality of \emph{naturally} emergent language
+in our experiments.
 %two different dedicated experiments, i.e., \note{XXX and XXX, are utilized for XXX}.
 %Regarding the experimental validation, it is conducted on a listener-speaker
 %referential game framework with eliminated unnatural inductions.
@@ -210,16 +210,16 @@ can generate a more compositional language with a higher probability.}
 In this paper, we made the following contributions:
 \begin{itemize}[topsep=0pt,itemsep=0cm]
 \item To our best knowledge, we are the first work to successfully achieve
-high compositional symbolic
+high compositional emergent
 language naturally, without any deliberately handcrafted induction.
-\item We analyze the compositionality of emerged symbolic language
+\item We analyze the compositionality of emergent 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
+capacity facilitates the emergence of language with higher
 compositionality.
 \end{itemize}
 
@@ -229,6 +229,6 @@ 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 novel mutual-information-based metric for measuring
-the compositionality of symbolic language. Section~\ref{sec:exp} gives the
+the compositionality of emergent 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.