Decision Flexibility
  The development of new methods and representations for temporal
decision-making requires a principled basis for characterizing and measuring
the flexibility of decision strategies in the face of uncertainty. Our goal in
this paper is to provide a framework - not a theory - for observing how
decision policies behave in the face of informational perturbations, to gain
clues as to how they might behave in the face of unanticipated, possibly
unarticulated uncertainties. To this end, we find it beneficial to distinguish
between two types of uncertainty: "Small World" and "Large World" uncertainty.
The first type can be resolved by posing an unambiguous question to a
"clairvoyant," and is anchored on some well-defined aspect of a decision frame.
The second type is more troublesome, yet it is often of greater interest when
we address the issue of flexibility; this type of uncertainty can be resolved
only by consulting a "psychic." We next observe that one approach to
flexibility used in the economics literature is already implicitly accounted
for in the Maximum Expected Utility (MEU) principle from decision theory.
Though simple, the observation establishes the context for a more illuminating
notion of flexibility, what we term flexibility with respect to information
revelation. We show how to perform flexibility analysis of a static (i.e.,
single period) decision problem using a simple example, and we observe that the
most flexible alternative thus identified is not necessarily the MEU
alternative. We extend our analysis for a dynamic (i.e., multi-period) model,
and we demonstrate how to calculate the value of flexibility for decision
strategies that allow downstream revision of an upstream commitment decision.
