  Complexity of the problem of choosing among uncertain acts is a salient
feature of many of the environments in which departures from expected utility
theory are observed. I propose and axiomatize a model of choice under
uncertainty in which the size of the partition with respect to which an act is
measurable arises endogenously as a measure of subjective complexity. I derive
a representation of incomplete Simple Bounds preferences in which acts that are
complex from the perspective of the decision maker are bracketed by simple acts
to which they are related by statewise dominance. The key axioms are motivated
by a model of learning from limited data. I then consider choice behavior
characterized by a "cautious completion" of Simple Bounds preferences, and
discuss the relationship between this model and models of ambiguity aversion. I
develop general comparative statics results, and explore applications to
portfolio choice, contracting, and insurance choice.
