\chapter{Probabilistic representation and reasoning (and burglars)}
\section{Bayesian network and the conditional probability tables}
\begin{figure}[H]
	\caption{Bayesian network, visual representation}
	\centering
	\includegraphics[scale=0.5]{d1.eps}
\end{figure}

\strut\\
\begin{tabular}{|l|ll|}
	\hline
	& \multicolumn{2}{c|}{Radio}\\
	Earthquake & T & F\\
	\hline
	T & $0.9998$ & $0.0002$\\
	F & $0.0002$ & $0.9998$\\
	\hline
\end{tabular}
%
\begin{tabular}{|l|ll|}
	\hline
	& \multicolumn{2}{c|}{$I_1$}\\
	Earthquake & T & F\\
	\hline
	T & $0.2$ & $0.08$\\
	F & $0$ & $1$\\
	\hline
\end{tabular}
%
\begin{tabular}{|l|ll|}
	\hline
	& \multicolumn{2}{c|}{$I_2$}\\
	Burglar & T & F\\
	\hline
	T & $0.95$ & $0.05$\\
	F & $0$ & $1$\\
	\hline
\end{tabular}
%
\begin{tabular}{|ll|ll|}
	\hline
	&& \multicolumn{2}{c|}{Burglar}\\
	i1 & i2 & T & F\\
	\hline
	T & T & $1$ & $0$\\
	T & F & $1$ & $0$\\
	F & T & $1$ & $0$\\
	F & F & $0$ & $1$\\
	\hline
\end{tabular}
%
\begin{tabular}{|l|ll|}
	\hline
	& \multicolumn{2}{c|}{Watson}\\
	Alarm & T & F\\
	\hline
	T & $0.8$ & $0.2$\\
	F & $0.4$ & $0.6$\\
	\hline
\end{tabular}
%
\begin{tabular}{|l|ll|}
	\hline
	& \multicolumn{2}{c|}{Gibbons}\\
	Alarm & T & F\\
	\hline
	T & $0.99$ & $0.01$\\
	F & $0.04$ & $0.96$\\
	\hline
\end{tabular}
