Elo always

Author: Juanvoid01

docs/AlphaDeepChess/Capitulos/AnalysisOfImprovements.tex

@@ -294,7 +294,7 @@ \section{Evaluation versus \textit{Stockfish}}
 
 \newpage
 
-\section{Engine elo rating in \textit{Lichess}}
+\section{Elo rating in \textit{Lichess}}
 
 \noindent We deployed the engine on \textit{Lichess}, the platform that allows engines to compete against both human players and other bots (see~\cref{sec:lichess}).
 

docs/AlphaDeepChess/Capitulos/ConclusionesTrabajoFuturo.tex

@@ -14,7 +14,7 @@ \chapter{Conclusiones y trabajo futuro}
     \item \textit{Búsqueda con reducciones de movimientos tardíos}: no mejoró el rendimiento, ya que nuestra heurística actual de ordenación de movimientos no es lo suficientemente fuerte como para soportar una poda tan agresiva.
 \end{itemize}
 
-\noindent El motor alcanzó una puntuación ELO de 1900 en \textit{Lichess} mientras se ejecutaba en una Raspberry Pi 5 con una tabla de transposición de 2GB, lo que demuestra su eficiencia incluso en hardware con recursos limitados.
+\noindent El motor alcanzó una puntuación Elo de 1900 en \textit{Lichess} mientras se ejecutaba en una Raspberry Pi 5 con una tabla de transposición de 2GB, lo que demuestra su eficiencia incluso en hardware con recursos limitados.
 
 \vspace{1em}
 

docs/AlphaDeepChess/Capitulos/ConclusionsFutureWork.tex

@@ -14,7 +14,7 @@ \chapter{Conclusions and future work}
     \item \textit{Search with Late Move Reductions}: did not improve performance, as our current move-ordering heuristic is not strong enough to support such aggressive pruning.
 \end{itemize}
 
-\noindent The engine achieved an ELO rating of 1900 on \textit{Lichess} while running on a Raspberry Pi 5 with a 2GB transposition table, demonstrating its efficiency even on resource-constrained hardware.
+\noindent The engine achieved an Elo rating of 1900 on \textit{Lichess} while running on a Raspberry Pi 5 with a 2GB transposition table, demonstrating its efficiency even on resource-constrained hardware.
 
 \vspace{1em}
 

docs/AlphaDeepChess/Capitulos/ContribucionesPersonales.tex

@@ -38,7 +38,7 @@ \section*{Juan Girón Herranz}
 
     \item Used Linux's \texttt{perf} tool, analyzed the CPU overhead of the different parts of the chess engine.
 
-    \item Compiled and deployed the engine on a Raspberry Pi 5, configuring it as a \textit{Lichess} bot. Running under limited hardware resources, the engine achieved competitive ELO ratings while demonstrating our code's efficiency and portability.
+    \item Compiled and deployed the engine on a Raspberry Pi 5, configuring it as a \textit{Lichess} bot. Running under limited hardware resources, the engine achieved competitive Elo ratings while demonstrating our code's efficiency and portability.
 
 \end{itemize}
 

docs/AlphaDeepChess/Capitulos/Introduccion.tex

@@ -9,7 +9,7 @@ \chapter{Introduction}\label{cap:introduction}
 
 \vspace{1em}
 
-\noindent We present \textit{AlphaDeepChess}, a chess engine based on minimax with alpha-beta pruning that relies solely on classical algorithms and implements optimization techniques based on current knowledge about chess engines. Notably, the engine has achieved an ELO rating of around 1900 on \textit{Lichess}, demonstrating its competitive strength among online chess engines.
+\noindent We present \textit{AlphaDeepChess}, a chess engine based on minimax with alpha-beta pruning that relies solely on classical algorithms and implements optimization techniques based on current knowledge about chess engines. Notably, the engine has achieved an Elo rating of around 1900 on \textit{Lichess}, demonstrating its competitive strength among online chess engines.
 
 \vspace{1em}
 

docs/AlphaDeepChess/Cascaras/abstract.tex

@@ -10,7 +10,7 @@ \section*{\tituloPortadaEngVal}
 
 \vspace{1em}
 
-The chess engine has been uploaded to the \textit{Lichess} platform, where \textit{AlphaDeepChess} achieved an ELO rating of 1900 while running on a Raspberry Pi 5 equipped with a 2GB transposition table.
+The chess engine has been uploaded to the \textit{Lichess} platform, where \textit{AlphaDeepChess} achieved an Elo rating of 1900 while running on a Raspberry Pi 5 equipped with a 2GB transposition table.
 
 \section*{Keywords}
 

docs/AlphaDeepChess/Cascaras/resumen.tex

@@ -10,7 +10,7 @@ \section*{\tituloPortadaVal}
 
 \vspace{1em}
 
-El motor ha sido subido a la plataforma \textit{Lichess}, donde \textit{AlphaDeepChess} ha alcanzado una puntuación ELO de 1900, ejecutándose en una Raspberry Pi 5 con una tabla de transposiciones de 2GB.
+El motor ha sido subido a la plataforma \textit{Lichess}, donde \textit{AlphaDeepChess} ha alcanzado una puntuación Elo de 1900, ejecutándose en una Raspberry Pi 5 con una tabla de transposiciones de 2GB.
 
 \section*{Palabras clave}