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- \documentclass{article}
- \usepackage[pdftex,active,tightpage]{preview}
- \setlength\PreviewBorder{2mm}
- \usepackage[utf8]{inputenc} % this is needed for umlauts
- \usepackage[ngerman]{babel} % this is needed for umlauts
- \usepackage[T1]{fontenc} % this is needed for correct output of umlauts in pdf
- \usepackage{amssymb,amsmath,amsfonts} % nice math rendering
- \usepackage{braket} % needed for \Set
- \usepackage{caption}
- \usepackage{algorithm}
- \usepackage{xcolor}
- \usepackage[noend]{algpseudocode}
- \usepackage{mathtools,bm}
- \DeclareMathOperator*{\argmax}{arg\,max}
- \DeclareCaptionFormat{myformat}{#3}
- \captionsetup[algorithm]{format=myformat}
- \begin{document}
- \begin{preview}
- \begin{algorithm}[H]
- \begin{algorithmic}
- \Require
- \Statex Sates $\mathcal{X} = \{1, \dots, n_x\}$
- \Statex Actions $\mathcal{A} = \{1, \dots, n_a\},\qquad A: \mathcal{X} \Rightarrow \mathcal{A}$
- \Statex Reward function $R: \mathcal{X} \times \mathcal{A} \rightarrow \mathbb{R}$
- \Statex Black-box (probabilistic) transition function $T: \mathcal{X} \times \mathcal{A} \rightarrow \mathcal{X}$
- \Statex Learning rate $\alpha \in [0, 1]$, typically $\alpha = 0.1$
- \Statex Discounting factor $\gamma \in [0, 1]$
- \Procedure{QLearning}{$\mathcal{X}$, $A$, $R$, $T$, $\alpha$, $\gamma$}
- \State Initialize $Q: \mathcal{X} \times \mathcal{A} \rightarrow \mathbb{R}$ arbitrarily
- \State Initialize $M: \mathcal{X} \times \mathcal{A} \rightarrow \mathcal{X} \times \mathbb{R}$ arbitrarily \Comment{Model}
- \While{$Q$ is not converged}
- \State Select $s \in \mathcal{X}$ arbitrarily
- \State $a \gets \pi(s)$ \Comment{Get action based on policy}
- \State $r \gets R(s, a)$ \Comment{Receive the reward}
- \State $s' \gets T(s, a)$ \Comment{Receive the new state}
- \State $Q(s, a) \gets (1 - \alpha) \cdot Q(s, a) + \alpha \cdot (r + \gamma \cdot \max_{a'} Q(s, a'))$
- \State $M(s, a) \gets (s', r)$
- \For{$i$ in range $1, \dots, N$}
- \State Select $(\tilde{s}, \tilde{a}) \in \mathcal{X} \times \mathcal{A}$ arbitrarily
- \State $(s', r) \gets M(\tilde{x}, \tilde{a})$
- \State $Q(\tilde{s}, \tilde{a}) \gets (1 - \alpha) \cdot Q(\tilde{s}, \tilde{a}) + \alpha \cdot (r + \gamma \cdot \max_{a'} Q(s', a'))$
- \EndFor
- \State Calculate $\pi$ based on $Q$ (e.g. $\varepsilon$-greedy)
- \EndWhile
- \Return $Q$
- \EndProcedure
- \end{algorithmic}
- \caption{Dyna-Q: Learn function $Q: \mathcal{X} \times \mathcal{A} \rightarrow \mathbb{R}$}
- \label{alg:dyna-q}
- \end{algorithm}
- \end{preview}
- \end{document}
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