extended shizzle uitgebreid

diff --git a/report/ass2-1.tex b/report/ass2-1.tex
index 1e15055..42931cc 100644 (file)
--- a/report/ass2-1.tex
+++ b/report/ass2-1.tex
@@ -209,20 +209,39 @@ P(i_1|burglar)+P(i_2|earthquake)(1-P(i_1|burglar)) =
 TODOOOOOOOOOOO %Ik weet niet of we i_1 en i_2 nog door iets anders vervangen
 % moeten worden.
 When you compare the output of AILog and of the variable elimination, you see
-that they are similar.
+that they are exactly the same. 
 
 \newpage
 \section{Burglary problem with extended information}
-Extending the problem with multiple houses, dependencies and cold night we get
-the following AILog representation:
+Extending the story with multiple houses and constraints about who wants to work
+ with who the following AILog representation:
 \inputminted[linenos,fontsize=\footnotesize]{prolog}{./src/burglary.ail}
-When thinking about the dependencies and successful burglaries we found out that
-there are only four possible successful burglaries. In the model we abstracted
-from the dependency layer and implemented the model in three layers. The first
-layer is the initial probability of every burglar. The second layer is the
-possible groups that lead to a successful burglary. The chances that Holmes'
-house is hit is the third layer. This results in the following probability for
-a burglary in Holmes' house.
+
+The following demandings on the sets of colleagues, limited the number of
+ possible groups to four:
+ 
+ \begin{itemize}
+       \item needs(joe, [])
+       \item needs(william, [])
+       \item needs(jack, [joe])
+       \item needs(averall, [jack, william])
+ \end{itemize}
+
+The only way that those people will burgler, is when those constraints are satisfied and when there are at least two people working. So the only combinations possible are then: 
+\begin{enumerate}
+       \item Joe and Jack
+       \item Joe and William
+       \item Joe, William and Jack
+       \item Joe, William, Jack and Averall.
+\end{enumerate}
+
+We implemented the extended story using a three layered model.\\
+\textit{Each day a burglar decides whether he wants to work or not, and on
+        average this happens only 5 days a week} 
+       Meaning that every burglar has the same initial working probability: 5/7 (see the first 5 lines of code).\\
+Then we implemented the constraints on the colleagues by telling ailog that a burglary can happen when at least one of our combinations is working (see line 8 to 11).\\
+\textit{Finally, if they decide to burgle, then they will burgle 3 houses a night.} The third layer consists of implementing the change that out of the 10,000 houses in which Joe, William, Jack and Averall are the only burglars, Holmes' house is burgled as one of the three (see line 14 to 19).\\
+This results in the following probability for a burglary at a Holmes' house.
 
 $P(burglary)\cdot(
        P(\text{first house Holmes'})+

diff --git a/report/report.tex b/report/report.tex
index 2505c96..f1a08a6 100644 (file)
--- a/report/report.tex
+++ b/report/report.tex
@@ -8,10 +8,10 @@
 \usepackage{amsmath}
 \usepackage{amssymb}
 \usepackage[hidelinks]{hyperref}
-%\usepackage{epstopdf}
+\usepackage{epstopdf}
 %\usepackage{cleveref}
 
-%\renewcommand{\arraystretch}{1.3}
+\renewcommand{\arraystretch}{1.3}
 
 \author{
        Lubbers, M.\\