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If family time is more important, he will prefer
f
. Similarly, to determine a preference
between
e
and
h
, we need to know whether status or family time is more important.
The company Jones has two major interests: it needs a manager and it has to cut back
on expenses. These interests relate directly (one-to-one) to high position and low salary.
The ceteris paribus preference ordering for Jones is displayed in Figure 1b.
The Added Value of Interests.
It may seem that using interests next to issues just in-
troduces an extra layer in reasoning. From the issues and the relations between issues
and interests, we derive the interests that are met by outcomes, and from that we derive
preferences. Would it not be easier to derive the preferences directly from the issues?
We could just state that Jones has the interests of high position and low salary, option-
ally with an ordering between them, and we would be able to derive Jones' preferences
from that. This is because in this case there is a one-to-one relation between interests
and issues: every interest is met by exactly one issue, and every (relevant) issue meets
exactly one interest.
There are good reasons, however, why this approach is not always a good solution.
Consider for example Mark's preferences. A high salary satisfies both wealth and sta-
tus, and status can be satisfied by either a high salary or a high position. Because of
this, the (partial) preference ordering we determined for Mark cannot be defined as a
ceteris paribus ordering if the issues are taken as criteria. This is because high position
as criterion is dependent on high salary: if the salary is not high, then high position is a
distinguishing criterion, but if the salary is high, high position is not relevant anymore,
since the only interest that it serves, status, is already satisfied by high salary. So with a
fixed set of issues as criteria, ceteris paribus or lexicographic models cannot represent
every preference order. In many cases, this can be solved intuitively by taking underly-
ing interests into account.
There are other approaches to deal with this matter. Instead of assuming indepen-
dence of the criteria, one can also model conditional preferences, where criteria may
be dependent on other criteria. A well-known approach to represent conditional pref-
erences is CP-nets [16], which is short for conditional ceteris paribus preference net-
works. A CP-net is a graph where the nodes are variables (comparable to our notion of
issues). Every node is annotated with a conditional preference table, which lists a user's
preferences over the possible values of that variable. If such preferences are conditional
(dependent on other variables), each condition has a separate entry in the table, and the
variables that influence the preference are parent nodes of this variable in the graph. In
[16], an example of conditional preference is given regarding an evening dress. A man
unconditionally prefers black to white as a colour for both the jacket and the pants. His
preference between a white and a red shirt is conditioned on the combination of jacket
and pants. If they have the same colour, he prefers a red shirt (for a white shirt will make
his outfit too colourless). If they are of different colours, he prefers a white shirt (be-
cause a red shirt will make his outfit too flashy). The complete assignments (outcomes
in our terminology) are listed in Table 2a. The preference graph induced by the CP-net
for this example is displayed in Figure 2a.
We propose to replace the variables the preferences over which are conditional
with underlying interests - the reason for the dependency. In the evening dress ex-
ample, the underlying interest is that the colours of jacket, pants and shirt make a good
