2 \chapter{Probabilistic representation and reasoning (and burglars)
}
3 \section{Bayesian network and the conditional probability tables
}
5 \caption{Bayesian network, visual representation
}
7 %\includegraphics[scale=0.5]{d1.eps}
10 \begin{tabular
}{|l|ll|
}
12 &
\multicolumn{2}{c|
}{Radio
}\\
15 T & $
0.9998$ & $
0.0002$\\
16 F & $
0.0002$ & $
0.9998$\\
20 \begin{tabular
}{|l|ll|
}
22 &
\multicolumn{2}{c|
}{$I_1$
}\\
30 \begin{tabular
}{|l|ll|
}
32 &
\multicolumn{2}{c|
}{$I_2$
}\\
40 \begin{tabular
}{|ll|ll|
}
42 &&
\multicolumn{2}{c|
}{Alarm
}\\
43 $I_1$ & $I_2$ & T & F\\
52 \begin{tabular
}{|l|ll|
}
54 &
\multicolumn{2}{c|
}{Watson
}\\
62 \begin{tabular
}{|l|ll|
}
64 &
\multicolumn{2}{c|
}{Gibbons
}\\