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docs/AlphaDeepChess/Capitulos/DescripcionTrabajo.tex

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@@ -212,7 +212,7 @@ \section{Evaluation: materialistic approach}\label{sec:evaluation}
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\noindent Where $V(x)$ denotes the value of piece $x$.
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\subsection*{Piece square tables (PST's)}
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\subsection*{Piece square tables (PSTs)}
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\noindent The basic material evaluation described earlier has a significant limitation, it does not consider the fact that a piece could have more power in different squares of the board. For instance, as illustrated in the following image, a knight placed in the center can control up to eight squares, while a knight positioned in the corner can reach only two.
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@@ -226,7 +226,7 @@ \subsection*{Piece square tables (PST's)}
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markmoves={h8-g6,h8-f7,d4-b5,d4-b3,d4-c2,d4-c6,d4-e6,d4-e2,d4-f5,d4-f3},
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arrow=to
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]
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\caption*{Knight's movement on corner vs in center.}\label{fig:knight-movement-corner-and-center}
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\caption*{Knight's movement on corner vs in the center.}\label{fig:knight-movement-corner-and-center}
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\end{figure}
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\noindent The solution is to add a bonus or a penalization to the piece depending on the square it occupies. This is called a piece square table (PST). For each piece type, a PST assigns a positional bonus based on the square it occupies. These tables are typically implemented as arrays indexed by square and piece type~\cite{PieceSquareTables}.

docs/AlphaDeepChess/Capitulos/ImprovementTechniques.tex

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@@ -153,7 +153,7 @@ \subsection*{Magic bitboards}
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\vspace{1em}
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\noindent Magic bitboards technique used to reduce the size of the look up table. We cut off unnecesary information in the blockers bitboard, excluding the board borders and the squares outside its attack pattern.
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\noindent Magic bitboards technique used to reduce the size of the look up table. We cut off unnecessary information in the blockers bitboard, excluding the board borders and the squares outside its attack pattern.
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\vspace{1em}
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docs/AlphaDeepChess/Capitulos/Introduccion.tex

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@@ -43,7 +43,7 @@ \section{Work plan}
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\item Analyze the results and write the final report.
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\end{enumerate}
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\noindent In the following~\cref{sec:basicConcepts}, we will explain about the basic concepts of chess, but if you already have the knowledge we recommend you to advance directly to the next~\cref{cap:estadoDeLaCuestion}.
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\noindent In the following~\cref{sec:basicConcepts}, we will explain about the basic concepts of chess, but if you already have the knowledge, we recommend to advance directly to the next~\cref{cap:estadoDeLaCuestion}.
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\section{Chess fundamentals}\label{sec:basicConcepts}
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docs/AlphaDeepChess/Cascaras/abstract.tex

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@@ -14,4 +14,4 @@ \section*{\tituloPortadaEngVal}
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\section*{Keywords}
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\noindent chess, artificial intelligence, chess engine, alpha-beta pruning, iterative deepening, quiescence search, move ordering, transposition table, zobrist hashing, magic bitboards
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\noindent chess, artificial intelligence, chess engine, alpha-beta pruning, iterative deepening, quiescence search, move ordering, transposition table, Zobrist hashing, magic bitboards

docs/AlphaDeepChess/Cascaras/agradecimientos.tex

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\chapter*{Acknowledgments}
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\noindent To the Chess programming Wiki for its extensive repository of high-level resources on chess engine development~\cite{ChessProgrammingWiki}.
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\noindent To the Chess Programming Wiki for its extensive repository of high-level resources on chess engine development~\cite{ChessProgrammingWiki}.
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\vspace{1em}
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docs/AlphaDeepChess/Cascaras/resumen.tex

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\section*{Palabras clave}
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\noindent ajedrez, inteligencia artificial, motor de ajedrez, poda alfa-beta, búsqueda en profundidad iterativa, búsqueda quiescente, ordenación de movimientos, tabla de transposiciones, zobrist hashing, bitboards mágicos
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\noindent ajedrez, inteligencia artificial, motor de ajedrez, poda alfa-beta, búsqueda en profundidad iterativa, búsqueda quiescente, ordenación de movimientos, tabla de transposiciones, Zobrist hashing, bitboards mágicos

docs/AlphaDeepChess/TFGTeXiS.pdf

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include/move_generator/magic_bitboards.hpp

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* This technique is used to optimize the memory space of the lookup table of rook and bishop moves.
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*
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* The lookup table is indexed by piece square and the blockers bitboard (pieces that block the path of the piece).
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* We cut off unnecesary information like the board borders and the squares outside its attack pattern.
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* We cut off unnecessary information like the board borders and the squares outside its attack pattern.
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* Optimally we could use 11 bits for bishop moves (2048 > 1428) and 13 bits for rooks (8196 > 4900).
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*
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* A magic number is a multiplier to the index with the following property:
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* - keeps intact the important info about the blockers (the nearest blockers to the piece are intact).
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* For example: [Rook] -> -> -> [pawn1][pawn2].
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* In this case pawn2 is an unnecesary piece inside the blockers bitboard, because the piece that actually
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* In this case pawn2 is an unnecessary piece inside the blockers bitboard, because the piece that actually
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* block the path of the rook is pawn1.
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*
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* - Reduces the index number close to the optimal size (ideally to fit inside 11 or 13 bits)
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*/
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inline uint64_t magic_index_rook(uint64_t blockers, Square rook_square, uint64_t rook_attacks)
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{
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// we cut unnecesary information to optimize memory space: board edges and squares outside the attack mask.
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// we cut unnecessary information to optimize memory space: board edges and squares outside the attack mask.
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const uint64_t edges = ((ROW_1_MASK | ROW_8_MASK) & ~get_row_mask(rook_square.row())) |
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((COL_A_MASK | COL_H_MASK) & ~get_col_mask(rook_square.col()));
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blockers &= rook_attacks & ~edges;
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*/
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inline uint64_t magic_index_bishop(uint64_t blockers, Square bishop_square, uint64_t bishop_attacks)
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{
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// we cut unnecesary information to optimize memory space: board edges and squares outside the attack mask.
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// we cut unnecessary information to optimize memory space: board edges and squares outside the attack mask.
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const uint64_t edges = ((ROW_1_MASK | ROW_8_MASK) & ~get_row_mask(bishop_square.row())) |
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((COL_A_MASK | COL_H_MASK) & ~get_col_mask(bishop_square.col()));
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