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dences
E
=
{
(Director = Spielberg)
∧
(Type = S.F.)
}
,
and Example 3.6, where the experience
I
3
of agent
A
3
are represented
by the rules R1 to R6, we see that rule R1 and rule R2 are fired, and
the corresponding opinion of the agent
A
3
is therefore
B
3
=
{
Good
,
Averge
}
.
Note that this does not intend to mean
A
3
believes the probability of
any other state value other than 'Average' or 'Good' must be zero.
This does not imply that the probability that the quality of the cur-
rent movie is average, and that is good, are both
1
2
,either.Inmost
applications including the current scenario, the obtained samples (i.e.,
the agents' experience rules) are far too sparse to provide any mean-
ingful assessment to the probabilistic distribution of the state values.
Rather, the opinion
B
3
=
{
Good
,
Averge
}
should be understood as the following statement from agent
A
3
:'From
my (i.e., agent
A
3
's) limited (self-conflicting) experience so far, I have
reason to believe the quality of the current movie (i.e., state) may be
either average or good.'
The situation for agent
A
1
is simpler. As evidences
Example 3.8
are
E
=
{
(Director = Spielberg)
∧
(Type = S.F.)
}
in Example 3.5, there are totally 3 rules in agent
A
1
's experience rules
that are fired, which correspond to the previous cases when agent
A
1
watched
E.T. the Extra-Terrestrial
,
The Lost World
,and
Jurassic
Park
. Hence the corresponding opinion of agent
A
1
is
B
1
=
{
Good
,
Good
,
Good
}
,
or simply
{
Good
}
. It is important to note that, again, this does
not
in-
tend to mean that agent
A
1
believes the probability that the quality of
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