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%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
\usepackage[normalem]{ulem}     % For underlining links
% Most of the following are not required for the majority
% of cheat sheets but are needed for some symbol support.
\usepackage{amsmath}            % Symbols
\usepackage{MnSymbol}           % Symbols
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% Document Info
\author{RobinX}
\pdfinfo{
  /Title (reinforcement-learning-cheat-sheet.pdf)
  /Creator (Cheatography)
  /Author (RobinX)
  /Subject (Reinforcement Learning Cheat Sheet)
}

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% Header and Footer
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\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{C}
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    \vspace{-7pt}
    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
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\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Reinforcement Learning Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{RobinX} via \textcolor{DarkBackground}{\uline{cheatography.com/146714/cs/31778/}}}
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\fancyfoot[L]{ \footnotesize
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{LL}
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  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}RobinX \\
  \uline{cheatography.com/robinx} \\
  \end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 21st April, 2022.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
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  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
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\end{multicols}}




\begin{document}
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% Set font size to small. Switch to any value
% from this page to resize cheat sheet text:
% www.emerson.emory.edu/services/latex/latex_169.html
\footnotesize % Small font.


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\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Terminology}}  \tn
% Row 0
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Agent & Pelaku \tn 
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Reward & Hadiah \tn 
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Action & Tindakan \tn 
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State & Keadaan \tn 
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Environment & Lingkungan \tn 
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Eksploitasi & Aksi algoritme RL dalam menggunakan aksi sebelumnya yang mendapat reward positif. \tn 
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% Row 6
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Ekplorasi & Aksi algoritme RL dalam melakukan aksi berbeda untuk mencari reward positif yang lain. \tn 
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% Row 7
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Policy & Rules (aturan) atau strategi yang digunakan oleh agent untuk melakukan action (A) selanjutnya, berdasarkan state (S) saat ini. \tn 
% Row Count 18 (+ 5)
% Row 8
\SetRowColor{LightBackground}
Value function (V) & Total nilai jangka panjang yang diharapkan (expected longterm return without discount) dari state saat ini di bawah policy 𝜋. Value ini adalah kebalikan dari short-term reward (R). \tn 
% Row Count 26 (+ 8)
% Row 9
\SetRowColor{white}
Optimal Value Function & Sebuah fungsi yang memiliki nilai tertinggi untuk semua state dibandingkan dengan fungsi nilai lainnya. \tn 
% Row Count 30 (+ 4)
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\par\addvspace{1.3em}

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Optimal Policy & Policy (kebijakan) yang memiliki fungsi nilai optimal. \tn 
% Row Count 3 (+ 3)
% Row 11
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Model Environment & Segala sesuatu yang meniru perilaku environment. Atau, secara umumnya, sebuah kesimpulan tentang bagaimana perilaku dari environment. \tn 
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% Row 12
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Model Based RL & Model dasar atau paling sederhana dan memiliki perencanaan terhadap tindakannya, atau dapat juga dimaknai sebagai agent mengeksploitasi informasi yang dipelajari sebelumnya untuk menyelesaikan tugasnya. \tn 
% Row Count 17 (+ 8)
% Row 13
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Model Free RL & Kebalikan dari model Model Based RL, karena agent belajar dari lingkungan melalui metode trial and error untuk memperoleh pengalamannya. \tn 
% Row Count 23 (+ 6)
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\end{document}