diff --git a/doc/report/main.tex b/doc/report/main.tex
index fcc3a3e1bf97a9bd03874b7effcb25a0148456a4..cac1600b426a73e1598cb5a0ec23563c90a8988c 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