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The above property will be used in Sect. 3.7 to give a metric characterisation of
probabilistic bisimulation (cf. Theorem 3.11 ).
In the remainder of this subsection we do a sanity check and show that ( 3.7 ) and
( 3.8 ) do entail the same metric on
( S ). Given a metric m on S , we write m for the
lifted metric by using the linear programming problem in ( 3.8 ).
D
Proposition 3.5
Let m be a metric over S. Then
m is a metric over
ˆ
D
( S ) .
Proof
We verify that (
D
( S ),
m ) satisfies the definition of pseudometric space.
ˆ
1. It is clear that
m ( ʔ , ʔ )
ˆ
=
0.
2. We observe that
s S ( ʔ ( s )
s S ( ʔ ( s )
s S ʔ ( s )
s S ʔ ( s )
ʔ ( s )) x s =
ʔ ( s ))(1
x s )
+
s S ( ʔ ( s )
=
ʔ ( s ))(1
x s ) .
Now x s =
1
x s also satisfy the constraints on x s in ( 3.7 ), hence the symmetry
ˆ
m can be shown.
3. Let ʔ 1 , ʔ 2 , ʔ 3 D
of
( S ), we have
( ʔ 1 ( s )
ʔ 3 ( s )) x s =
( ʔ 1 ( s )
ʔ 2 ( s )) x s +
( ʔ 2 ( s )
ʔ 3 ( s )) x s .
s
S
s
S
s
S
By taking the maximum over the x s for the left hand side, we obtain
m ( ʔ 1 , ʔ 3 )
m ( ʔ 1 , ʔ 2 )
+ m ( ʔ 2 , ʔ 3 ) .
Let m be a metric over S. Then m
Proposition 3.6
is a metric over
D
( S ) .
( S ), m ) satisfies the definition of pseudometric space.
1. It is easy to see that m ( ʔ , ʔ )
Proof
We verify that (
D
=
0, by letting y s , s =
ʔ ( s ) and y s , t =
0 for all
t in ( 3.8 ).
2. Suppose m ( ʔ , ʔ ) is obtained by using some real numbers y s , t in ( 3.8 ). Let
y s , t =
s
=
y t , s for all s , t
S . We have that
y t , s =
y t , s .
m ( s , t )
·
y s , t =
m ( s , t )
·
m ( t , s )
·
s , t S
s , t S
t , s S
Observe that s S y t , s = s S y s , t =
ʔ ( t ) for all t
S , and similarly we have
the dual t S y t , s = ʔ ( s ) for all s S . It follows that m ( ʔ , ʔ )
= m ( ʔ , ʔ ).
3. Suppose m ( ʔ 1 , ʔ 2 ) is obtained by using some real numbers x s , t in ( 3.8 ), and
m ( ʔ 2 , ʔ 3 ) is obtained by using y s , t . Let z s , t = r ʔ 2 x s , r ·
y r , t
ʔ 2 ( r ) . Note that
if ʔ 2 ( r )
=
0 for some r
S , then we must have that x s , r =
y r , t =
0 for any
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