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writeup/P2 Proposal.tex

@@ -70,30 +70,24 @@ scale of 1 to 10,  10 being favorite and 1 being least favorite'.  Furthermore,
 
 %daniel is here
 \paragraph*{Knowledge Engineering}
+We model the diners' various taste preferences using
+a Bayes net. We model the taste
 
-We model the diners' various taste preferences preferences using
-a Bayes net. In the first layer in Figure \ref{img:bayes_net}
-we capture control variables such as vegarian or allergy to nuts.
-These were modeled as boolean variables, with 'true' indicating the presence of a constraint.
-
-Our model consists of 4 layers, 
-each modeling a different aspect of taste or dietary requirement.
 \begin{description}
-\item[Layer 1] General meal preferences such as
-being vegetarian or being allergic to nuts.
-
-\item[Layer 2] The second layer models a general preference towards 
+\item[Layer 1] The first layer models a general preference towards 
 different food categories like vegetables or meat.
 As one can see, the food categories are dependent 
 on the general meal preference. For example 
 being vegetarian will exclude meat and will 
 support vegetables.
 
-\item[Layer 3]  Specific flavors and ingredients. Each ingredient is conditioned 
+\item[Layer 2]  Specific flavors and ingredients. Each ingredient is conditioned 
 by the food category to which it belongs.
-
 \end{description}
 
+If we need to model hard constraints, like 
+
+
 The overall net is shown in Figure \ref{img:bayes_net}.
 Given a recipe with a list of ingredients $I = i_1,...,i_n$ 
 and a Bayesian network capturing user preferences