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a constant polynomial, it must depend on at least one of these variables, say x i,j 1 . Then the poly-
nomial P( 1 ) must also depend on x i,j 1 . Similarly, the polynomial P( 2 ) must depend on some
variable x i,j 2 , with the same index i . Then, the identity P( 1 )
2 ) implies that
the latter polynomial contains the product x i,j 1 · x i,j 2 , violating either condition (a) (when j 1 = j 2 )
or condition (b) (when j 1 =
·
P( 2 )
=
P( 1
j 2 ), which is a contradiction. This proves the claim.
5.1.1.2 Rule 3: Disjoint OR
To motivate the next heuristics, consider the formula 3 X ∧¬ Y X Y above. Since the
two events
¬ X ∧¬ Y and X Y are disjoint probabilistic events, we have:
P( 3 ) = P( ¬ X ∧¬ Y) + P(X Y) = ( 1 P(X)) · ( 1 P(Y)) + P(X) · P(Y)
Two propositional formulas 1 , 2 are called disjoint if the formula 1 2 is
Definition 5.5
not satisfiable.
The disjoint-or rule is the following. If 1 , 2 are disjoint formulas, then:
Disjoint-or:
P( 1 2 ) = P( 1 ) + P( 2 )
(5.3)
5.1.1.3 Rule 4: Negation
It is easy to push the probability operator past negation:
P( ¬ ) =
P ()
Negation:
1
(5.4)
5.1.1.4 Rule 5: Shannon Expansion
We illustrate Shannon's expansion using the following example: = XY XZ YZ .None
of our prior rules apply immediately here. Instead, we write it as a disjoint-or: = (
X) ( ∧¬ X) ; hence, P () = P( X) + P( ∧¬ X) . Denote | X = Y Z YZ Y
Z the formula obtained from by substituting X with true . Similarly, | ¬ X = YZ . Then,
we have P () = P( | X X) + P( | ¬ X ∧¬ X) = P(Y Z) · P(X) + P(YZ) · ( 1 P(X)) =
( 1
( 1
P(X)) .
In general, given a propositional formula , a random variable X , and a value a
P(Y))
·
( 1
P (Z)))
·
P(X)
+
P(Y)
·
P(Z)
·
( 1
Dom X ,
denote
| X = a the formula obtained from by substituting all occurrences of X with a . Note that
the formula | X = a
does not depend on the variable X : X
Va r ( | X = a )
Let Dom X ={ a 0 ,a 1 ,...,a m }
Definition 5.6
. Then the Shannon expansion of a propositional
formula is:
| X = a 0 (X = a 0 ) | X = a 1 (X = a 1 ) ... | X = a m (X = a m )
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