From b06a3cae4dc263cb28bd5d01c920b18bcf5901e5 Mon Sep 17 00:00:00 2001
From: Alex <alexandravigneron1@gmail.com>
Date: Fri, 3 Jul 2020 09:45:14 +0200
Subject: [PATCH] abstract and intro plan
---
doc/report/main.tex | 6 ++++++
1 file changed, 6 insertions(+)
diff --git a/doc/report/main.tex b/doc/report/main.tex
index fcc3a3e..cac1600 100644
--- a/doc/report/main.tex
+++ b/doc/report/main.tex
@@ -186,6 +186,8 @@ Jean-Christophe \textsc{Routier} \\
\end{titlepage}
\begin{abstract}
+ This paper presents a short overview of DCOPs and details MGM and MGM-2 algorithms.
+ Both algorithms are presented with corresponding detailed automata and two afferent examples of execution.
\end{abstract}
%\maketitle
@@ -202,6 +204,10 @@ Several open-source implementations of MGM exist in Python with the \href{https:
Though not necessarily always the best performers, MGM and its variants are deemed robust and efficient algorithms on average, making them suitable benchmark options \cite{fioretto18jair}.
We hereby present the MGM and MGM-2 algorithms and detail two toy-examples to facilitate their analysis.
+We begin by giving a short overview of what DCOPs are and a general picture of the state of the art algorithms used to solve them.
+We then move on to a brief review of the existing algorithms to address DCOPs and detail two of these, namely MGM and MGM-2.
+We proceed to the description of the MGM-2 automaton and finally move on to two examples of execution of said algorithms.
+
\include{pb}
\newpage
--
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