From 6dcb89e722cc9ddf64596e95e74976bec9c1d1a1 Mon Sep 17 00:00:00 2001 From: Joe Moudrik Date: Mon, 10 Jun 2013 13:49:07 +0200 Subject: [PATCH] clanek: minor tweaks, citation fix and dinerchtein --- PAPERS/clanek_go_congress/clanek.tex | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/PAPERS/clanek_go_congress/clanek.tex b/PAPERS/clanek_go_congress/clanek.tex index 01169d0..af632a3 100644 --- a/PAPERS/clanek_go_congress/clanek.tex +++ b/PAPERS/clanek_go_congress/clanek.tex @@ -75,7 +75,7 @@ a contribution to Go-theoretical discussion on the scope of playing style''. \section{Introduction} The field of Computer Go usually focuses on the problem of creating a~program to play the game, finding the best move from a~given -board position \cite{GellySilver2008}. We focus on analyzing existing game +board position \citep{GellySilver2008}. We focus on analyzing existing game records with the aim of helping humans to play and understand the game better instead. @@ -128,7 +128,7 @@ This section presents the methods for extracting the evaluation vector (we call it $ev$) from a set of games. Because we aggregate data by player, each game in the set is accompanied by the color which specifies our player of interest. -The sample is therefore is regarded as a \emph{set +The sample is therefore regarded as a \emph{set of colored games}, $GC = \{ (game_1, color_1), \ldots\}$. The evaluation vector $ev$ is composed by concatenating several @@ -140,7 +140,7 @@ please see \citep{Moudrik13} for an extended description. \subsection{Raw Game Processing} The games\footnote{ - We use the standard \emph{.sgf} file format as input, \cite{SGF}. + We use the standard \emph{.sgf} file format as input, \citep{SGF}. } are processed by the Pachi Go Engine~\citep{Pachi} which exports a variety of analytical data about each move in the game. @@ -164,7 +164,7 @@ a certain distance.\footnote{ \label{grid} The distance is given by the {\em gridcular} metric $d(x,y) = |\delta x| + |\delta y| + \max(|\delta x|, |\delta y|)$, which produces -a circle-like structure on the Go board square grid \cite{SpatPat}. +a circle-like structure on the Go board square grid \citep{SpatPat}. Spatial patterns of sizes 2 to 6 are regarded. } @@ -277,7 +277,7 @@ size of the win or loss in points. The six numbers form the last feature. \label{sec:mach} So far, we have considered how we can turn a set of coloured games $GC$ into an evaluation vector. Now, we are going to show how to utilize the evaluation. -To predict various player attributes, we use start with an input dataset $D$ consisting +To predict various player attributes, we start with an input dataset $D$ consisting of pairs $D=\{ (GC_i, y_i), \dots\}$, where $GC_i$ corresponds to a set of colored games of $i$-th player and $y_i$ is the target attribute. The $y_i$ might be fairly arbitrary, as long as it has @@ -411,7 +411,7 @@ to the present. We chose a small subset of popular professional players (mainly from the 20th century) and asked several experts (professional and strong amateur players) to evaluate these players using a questionnaire. The experts (Alexander -Dinerschtein 3-pro, Motoki Noguchi 7-dan, +Dinerchtein 3-pro, Motoki Noguchi 7-dan, Vladim\'{i}r Dan\v{e}k 5-dan and V\'{i}t Brunner 4-dan) were asked to assess the players on four scales, each ranging from 1 to 10. -- 2.10.5.GIT