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/Title (Characterization Capacity of Agents and Compositionality from Naturally Emergent Communication)
/Author (AAAI Press Staff, Pater Patel Schneider, Sunil Issar, J. Scott Penberthy, George Ferguson, Hans Guesgen, Francisco Cruz, Marc Pujol-Gonzalez)
/TemplateVersion (2021.1)
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\title{Enabling the Emergence of Symbolic Language without Handcrafted Inductions}
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    %Authors
    % All authors must be in the same font size and format.
    %Written by AAAI Press Staff\textsuperscript{\rm 1}\thanks{With help from the AAAI Publications Committee.}\\
    %AAAI Style Contributions by Pater Patel Schneider,
    %Sunil Issar,  \\
    %J. Scott Penberthy,
    %George Ferguson,
    %Hans Guesgen,
    %Francisco Cruz,
    %Marc Pujol-Gonzalez
    %\\
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\begin{document}
\linenumbers

\maketitle

\begin{abstract}
 The emergence of symbolic languages with high compositionality has
  attracted extensive attention from a broad range of communities. Existing
  studies achieve high compositionality through \emph{deliberately handcrafted}
  inductions (e.g., small vocabulary sizes, addtional rewards, constructed 
  loss functions and ease-of-teaching) in multi-agent learning, which are unnatural. 
  Yet, few studies investigate the emergence of symbolic language with high
  compositionality \emph{naturally}, i.e., without deliberately handcrafted
  inductions. 
  
  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
  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}
  between the agent capacity and the compositionality of symbolic language, with
  a novel mutual information-based metric for 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
  %novel mutual information-based metric for the compositionality.
  %The
  %experiments are conducted on a listener-speaker referential game framework
  %with eliminated external environment factors.
  %With a novel mutual information-based metric for the compositionality, 
  The experimental results lead to a counter-intuitive conclusion that lower agent
  capacity facilitates the emergence of symbolic language with higher
  compositionality. \note{Based on our conclusion, we can generate higher
  compositional symbolic language with a higher probability.}


%  The natural emergence of symbolic languages with high compositionality has
%  attracted extensive attentions from a broad range of communities. Existing
%  studies only investigated the impacts of \emph{deliberately designed} external
%  environmental factors (e.g., small vocabulary sizes, carefully constructed
%  distractors, and ease-of-teaching), which may be too ideal to exist in the
%  real world, without considering the importance of internal capacity of agents.
%  
%  In this paper, we first reveal and characterize the quantitative relationship
%  between the agent capacity and the compositionality of symbolic language both
%  theoretically and experimentally. The theoretical analysis is built on the MSC
%  (Markov Series Channel) model for the language transmission process and a
%  novel mutual information-based metric for the compositionality. The
%  experiments are conducted on a listener-speaker referential game framework
%  with eliminated external environment factors. 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{abstract}

\input{tex/introduction.tex}
\input{tex/relatedwork.tex}
\input{tex/theory.tex}
\input{tex/theory2.tex}
\input{tex/experiments.tex}
\input{tex/last.tex}

%\clearpage
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\bibliography{ref.bib}

\end{document}
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