% the document class file should have been included in the latex distribution
\documentclass[sigconf]{acmart}

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\usepackage{url}
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%% \BibTeX command to typeset BibTeX logo in the docs
\AtBeginDocument{%
\providecommand\BibTeX{{%
		\normalfont B\kern-0.5em{\scshape i\kern-0.25em b}\kern-0.8em\TeX}}}

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%% block for ACM information declaration
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\setcopyright{none} %acmcopyright
\acmYear{2020}
\acmConference[DAI '20]{Second International Conference on Distributed Artificial Intelligence}{October 24-27, 2020}{Nanjing, China}
\acmBooktitle{Second International Conference on Distributed Artificial Intelligence (DAI '20), October 240--27, 2020, Nanjing, China}
%\acmPrice{15.00}
%\acmDOI{xx.xxxx/xxxxx.xxxxx}
%\acmISBN{xxx-x-xxxx-xxxx-x/xx/xx}

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%% Paper title and authors block
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\begin{document}
\title{Template of DAI 2020 Submissions}
\titlenote{title notes are put here.}

% Yi-Qi Hu, Hong Qian and Yang Yu
\author{Author 1}
\affiliation{%
	Affiliation
}
\email{email@address}

\author{Author 2}
\affiliation{%
	Affiliation
}
\email{email@address}

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%% The abstract is a short summary of the work to be presented in the article.
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\begin{abstract}
    The abstract is a short summary of the work to be presented in the article. The abstract is a short summary of the work to be presented in the article. The abstract is a short summary of the work to be presented in the article. The abstract is a short summary of the work to be presented in the article. The abstract is a short summary of the work to be presented in the article.
\end{abstract}
\begin{CCSXML}
	<ccs2012>
	<concept>
	<concept_id>10003752.10003809.10003716.10011138.10011140</concept_id>
	<concept_desc>Theory of computation~Nonconvex optimization</concept_desc>
	<concept_significance>500</concept_significance>
	</concept>
	<concept>
	<concept_id>10003752.10003809.10010170</concept_id>
	<concept_desc>Theory of computation~Parallel algorithms</concept_desc>
	<concept_significance>500</concept_significance>
	</concept>
	</ccs2012>
\end{CCSXML}

\ccsdesc[500]{Theory of computation~Parallel algorithms}
\ccsdesc[500]{Theory of computation~Nonconvex optimization}

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%% Keywords. The author(s) should pick words that accurately describe
%% the work being presented. Separate the keywords with commas.
\keywords{keyword 1, keyword 2, keyword 3, keyword 4, keyword 5}

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\maketitle

\section{Introduction}

The aim of the Distributed Artificial Intelligence (DAI) is bringing together researchers and practitioners in related areas (general AI, multi-agent systems, distributed learning, economics and computation, reinforcement learning, etc) to provide a single, high-profile, internationally renowned forum for research in the theory and practice of distributed AI. The second conference will be located in Nanjing China in October 2020. To maintain the high quality of the conference, we will invite high quality tutorials and invite accepted papers at sister conferences (e.g., AAMAS, AAAI, IJCAI, EC, KDD, ICML, NeurIPS) to present at the conference. We will also invite high quality talks from leading industrial researchers.


\section{Information for Authors}
DAI 2020 encourages the submission of theoretical, empirical, and perspective papers. Submitted papers should make clear the significance and relevance of their results to the scope and agenda of the DAI conference. Each paper should have a thorough evaluation, either theoretical or empirical, that advances the current understanding of distributed AI. Each paper should also pay attention to discussing how their work relates to the current AI literature. All submissions will be rigorously peer reviewed and evaluated on the basis of the overall quality of their technical contribution, including criteria such as originality, soundness, relevance, significance, quality of presentation, and understanding of the state of the art.

The abstract submission deadline is May 10, 2020 (23:59 UTC-12). By this time, authors are asked to submit their paper to: \\ \url{https://easychair.org/conferences/?conf=dai2020}

The initial paper needs to be submitted by this date; however, authors are encouraged to update their submission as desired after the review period. Please note that submitting an abstract is required before submitting a full paper.

To submit a paper, please first create an Easychair.org account, login to your account and go to the submission page to submit your paper.

The paper length is limited to 6 pages, with 1 additional page containing only bibliographic references. Authors may use as many pages of appendices (after the bibliography) as they wish, but reviewers are not required to read these.

The DAI 2020 review process is DOUBLE BLIND. Please make sure that the submission does not disclose the author's identities or affiliation.

Please include any supplementary material after the main paper in the same PDF. Please note that the reviewers are not required to read this extra material when assessing the paper.

All work must be original, i.e., it must not have appeared in a conference proceedings, book, or journal and may not be under review for another archival conference. At least one of the authors of each paper is required to register, attend, and present the paper at the conference.

\section{Topics of Interest}

The conference solicits papers addressing original research on distributed Artificial Intelligence. Topics of interest include (but are not limited to) the following:

Agent Cooperation:
\begin{itemize}
\item 	Biologically-inspired approaches and methods
\item 	Collective intelligence
\item 	Distributed problem solving
\item 	Teamwork, team formation, teamwork analysis
\item 	Coalition formation (non-strategic)
\item 	Multi-robot systems
\end{itemize}

Humans and Agents:
\begin{itemize}
\item Human-robot/agent interaction
\item Multi-user/multi-virtual-agent interaction
\item Agents competing against humans
\item Agent-based analysis of human interactions
\item Agents for improving human cooperative activities
\item Applications
\end{itemize}

Single/Multiagent Learning:
\begin{itemize}
\item Reward structures for learning
\item Multiagent learning
\item Reinforcement learning
\item Deep learning
\item Adversarial machine learning
\item Applications
\end{itemize}

Computational game theory:
\begin{itemize}
\item Complexity of algorithms of games
\item Practical algorithms for games
\item Behavioral models of games
\item Security games
\item Applications
\end{itemize}

Economics and computation:
\begin{itemize}
\item Auctions and mechanism design
\item Market design and applications
\item Social choice theory
\item Game theory for practical applications
\item Economics of blockchain systems
\item Applications
\item Policies
\item Policy on multiple and previous submissions
\end{itemize}

\section{Conclusion}


 

%\subsubsection*{Acknowledgments}

%Do not include acknowledgments in the submission, only in the final paper.

\small
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\bibliographystyle{named} 
%\bibliography{bibfile}

\clearpage
\normalsize
\appendix
%\appendix
\section{Appendix}
\subsection{Appendix}
Appendix is allowed. However, reviewers are not required to read appendix.

\end{document}
\endinput
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%% End of file `sample-sigconf.tex'.
