If the preferences have been determined in a way consistent with the
axioms, then it can be shown that a utility function always
exists. This means that there exists a function
such that, for all
,
![]() ![]() |
(9.87) |
A reward function can be defined using a utility function, ,
as
. The utility function can
be converted to a cost function as
. Minimizing the expected cost, as was
recommended under Formulations 9.3 and
9.4 with probabilistic uncertainty, now seems justified
under the assumption that
was constructed correctly to
preserve preferences.
Unfortunately, establishing the existence of a utility function does
not produce a systematic way to construct it. In most circumstances,
one is forced to design by a trial-and-error process that
involves repeatedly checking the preferences. In the vast majority of
applications, people create utility and cost functions without regard
to the implications discussed in this section. Thus, undesirable
conclusions may be reached in practice. Therefore, it is important
not to be too confident about the quality of an optimal decision rule.
Note that if worst-case analysis had been used, then most of the problems discussed here could have been avoided. Worst-case analysis, however, has its weaknesses, which will be discussed in Section 9.5.3.
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Steven M LaValle 2020-08-14