Back to practice exercises.
1: Background Reading
2: Learning Goals
 Represent a simple problem in plate notation.
 Derive and draw a grounded belief network.
 Calculate probabilities from a problem in the independent choice logic representation.
3: Directed Questions
 In probabilistic relational models, do different individuals share the same probability parameters? [solution]
 What are the three components of a plate model? [solution]
 What type of dependency can a plate model not adequately represent? [solution]
4: Exercise: Movie Preferences
Suppose we have parametrized random variables likes(Person,Movie), young(Person) and genre(Movie,Genre) where there are 1000 people, 100 movies and 5 genres. Suppose young(Person) and genre(Movie,Genre) are parents of likes(Person,Movie).
 Draw this in plate notation. [solution]
 How many random variables are in the grounding of this model? [solution]
 Draw the grounding belief network assuming the population of Person is {sam,chris,kim} and the population of Movie is {terminator,rango}. [solution]
Consider the following fragment of independent choice logic theory:
likes(Person,Movie) < young(Person) & genre(Movie,action) & young_likes_action(Person,Movie).
prob young_likes_action(Person,Movie):0.7.
likes(Person,Movie) < ~young(Person) & genre(Movie,action) & old_likes_action(Person,Movie).
prob old_likes_action(Person,Movie):0.6.
likes(Person,Movie) < genre(Movie,comedy) & likes_comedy(Person,Movie).
prob likes_comedy(Person,Movie):0.8.
young(sam).
young(chris).
genre(terminator,action).
genre(rango,comedy).
where < means "if", ~ means "not", & means "and", and "prob a:p." means {a, ~a} is an alternative with P(a) = p.
 What is the probability of likes(sam,rango)? [solution]
 What is the probability of likes(chris,terminator)? [solution]
 What is the probability of likes(kim,terminator)? [solution]
5: Learning Goals Revisited
 Represent a simple problem in plate notation.
 Derive and draw a grounded belief network.
 Calculate probabilities from a problem in the independent choice logic representation.
