Polish talk a bit

This commit is contained in:
Markus Kaiser 2019-08-26 16:06:27 +02:00
parent ac2e9111a6
commit 1a86506447
5 changed files with 36 additions and 29 deletions

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@ -31,3 +31,14 @@
journaltitle = {Siemens AG, CT IC 4, Technical Report},
title = {The Wet Game of Chicken}
}
@article{kaiser_interpretable_2019,
abstract = {In this paper, we present a Bayesian view on model-based reinforcement learning. We use expert knowledge to impose structure on the transition model and present an efficient learning scheme based on variational inference. This scheme is applied to a heteroskedastic and bimodal benchmark problem on which we compare our results to NFQ and show how our approach yields human-interpretable insight about the underlying dynamics while also increasing data-efficiency.},
author = {Kaiser, Markus and Otte, Clemens and Runkler, Thomas and Ek, Carl Henrik},
date = {2019},
journaltitle = {Computational Intelligence and Machine Learning},
langid = {english},
pages = {6},
title = {Interpretable {{Dynamics Models}} for {{Data}}-{{Efficient Reinforcement Learning}}},
volume = {ESANN 2019 proceedings}
}

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@ -105,7 +105,7 @@
}
\includeonlyframes{policy}
% \includeonlyframes{summary}
\begin{document}
@ -136,7 +136,7 @@
\end{frame}
\begin{frame}[label=dynamics_posterior]{Multimodal System Dynamics}
\begin{frame}[label=dynamics_posterior]{Multimodal System Dynamics\footcite{kaiser_interpretable_2019}}
\centering
\includestandalonewithpath{figures/dynamics_posterior_cut}
\end{frame}
@ -146,17 +146,21 @@
\centering
\begin{columns}[T]
\begin{column}{.45\textwidth}
\centering
\includestandalone{figures/policy_quiver}
\begin{align}
\Fun*{R}{x, y} = x
\end{align}
22\% drop rate
\end{column}
\begin{column}{.45\textwidth}
\centering
\uncover<2>{
\includestandalone{figures/conservative_policy_quiver}
\begin{align}
\Fun*{R^\prime}{x, y} = \Fun*{R}{x, y} - 5 \cdot \Prob{\text{drop} \given x, y}
\end{align}
19\% drop rate
}
\end{column}
\end{columns}
@ -165,30 +169,30 @@
\begin{frame}[label=summary]{Data Association with Gaussian Processes}
\medskip
\begin{block}{Interaction with domain experts}
\begin{block}{Model for multimodal data}
\vspace{1ex}
\begin{columns}[c]
\begin{column}[c]{.5\textwidth}
\begin{itemize}
\item Incomplete system knowledge
\item Hierarchical priors
\item Interpretable sub-models
\item Separate models per mode
\item Predictive Associations
\item Scalable inference
\end{itemize}
\end{column}
\begin{column}[c]{.475\textwidth}
\centering
\includestandalonewithpath{figures/graphical_model_mdgp_tiny}
\includestandalonewithpath{figures/graphical_model_dagp_tiny}
\end{column}
\end{columns}
\end{block}
%
\begin{block}{Trustworthy decision making}
\begin{block}{Informed decision making}
\begin{columns}[c]
\begin{column}[c]{.5\textwidth}
\begin{itemize}
\item Uncertainty due to incomplete data
\item Hierarchical priors
\item Interpretable sub-models
\item Stochastic systems
\item Robust and efficient inference
\end{itemize}
\end{column}
\begin{column}[c]{.475\textwidth}

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@ -12,24 +12,16 @@
\def\datapath{\figurepath/data}
\tikzstyle{tiny random variable} = [random variable, inner sep=0pt, minimum size=13pt, font=\tiny]
\node[tiny random variable, observed, xshift=-2ex] (Xsn) at (1, 0.25) {$\rv{s}_t$};
\node[tiny random variable, observed, xshift=2ex] (Xan) at (1, 0.25) {$\rv{a}_t$};
\node[tiny random variable, observed] (Xn) at (1, 0) {$\rv{x_n}$};
\node[tiny random variable, observed] (yn) at (1, -3) {$\rv{y_n}$};
\begin{scope}[on background layer]
\node[plate, opacity=0.3, fit=(Xsn)(Xan)] (Xn) {};
\end{scope}
\node[tiny random variable, observed] (yn) at (.8, -3) {$\rv{s}_{t+1}$};
\node[tiny random variable, latent] (fnm) at (0, -1) {$\rv{f_n^{\pix{k}}}$};
\node[tiny random variable, latent] (ynm) at (0, -2) {$\rv{y_n^{\pix{k}}}$};
\node[tiny random variable, latent] (fnm) at (0, -1) {$\rv{f}_t^{\pix{k}}$};
\node[tiny random variable, latent] (sigmanm) at (1, -1) {$\rv{\sigma}_t^{\pix{k}}$};
\node[tiny random variable, latent] (ynm) at (0, -2) {$\rv{s}_{t+1}^{\pix{k}}$};
\node[tiny random variable, latent] (alphanm) at (2, -1) {$\rv{\lambda}_t^{\pix{k}}$};
\node[tiny random variable, latent] (an) at (2, -3) {$\rv{l}_t$};
\node[tiny random variable, latent] (alphanm) at (2, -1) {$\rv{\alpha_n^{\pix{k}}}$};
\node[tiny random variable, latent] (an) at (2, -3) {$\rv{a_n}$};
\draw[edge, directed] (Xn) -| (fnm);
\draw[edge, directed] (Xn) -- (sigmanm);
\draw[edge, directed] (sigmanm) -- (ynm);
\draw[edge, directed] (Xn) -| (alphanm);
\draw[edge, directed] (fnm) -- (ynm);
\draw[edge, directed] (alphanm) -- (an);
@ -40,8 +32,8 @@
\begin{scope}[on background layer]
\node[
yshift=3pt,
plate, inner sep=5pt,
% yshift=3pt,
plate, inner sep=3pt,
opacity=0.3,
fit=(fnm)(alphanm)(ynm),
label={[font=\small, opacity=0.3, anchor=south east]south east:K}

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@ -27,7 +27,7 @@
point meta={-abs(\thisrow{aR})},
] table[
ignore chars={\#}, col sep=space, x=Y, y=X,
] {\datapath/policy_quiver.dat};
] {\datapath/conservative_policy_quiver.dat};
\addplot[
quiver={%
@ -41,7 +41,7 @@
},
] table[
ignore chars={\#}, col sep=space, x=Y, y=X,
] {\datapath/policy_quiver.dat};
] {\datapath/conservative_policy_quiver.dat};
\end{axis}
% NOTE(mrksr): Hacky fix for tikzpicture in block

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@ -53,7 +53,7 @@
\node[text width=7cm] at (2.25, 0.5) {
\begin{description}
\item[Dynamics] Agent in a flowing river
\item[Goal] Get close to waterfall
\item[Goal] Get close to the waterfall
\item[State] $(x, y)$-position in $\R^2$
\item[Action] $(x, y)$-movement in $\R^2$
\end{description}