NAME:
11
e) (4 pt)
You now want to compute the distribution
P
(
A
) using variable elimination. List the factors that
remain before and after eliminating the variable
N
.
Before:
The initial factors are just the conditional probability tables of the Bayes’ net.
P
(
A
),
P
(
P

A
),
P
(
C

A
),
P
(
T

C
),
P
(
N

P,C
),
P
(
E

T,N
)
After:
First, all factors that include the variable
N
are joined together, yielding
P
(
E,N

P,C,T
)
Next, the variable
N
is summed out of this new factor, yielding
P
(
E

P,C,T
)
The remaining factors include this new factor and the unused original factors.
P
(
A
),
P
(
P

A
),
P
(
C

A
),
P
(
T

C
),
P
(
E

P,C,T
)
Referring to the ﬁnal factor as
m
(
E,P,C,T
)
(like in the textbook) was also accepted.
f) (2 pt)
Pacman’s new diet allows only fruit (
P
and
A
) to be eaten, but Pacman only follows the diet
occasionally. Add the new variable
D
(for whether he follows the diet) to the network below by adding arcs.
This is the end of the preview.
Sign up
to
access the rest of the document.
 Spring '08
 Staff
 Artificial Intelligence, Conditional Probability, 2 Pt, 4 pt, unused original factors

Click to edit the document details