Abstract:

We introduce and characterize complexity constrained expected utility (CCEU) theory. Our representation can be interpreted as if the decision maker refines their understanding of an act (or lottery) by forming a partition of the set of outcomes and then taking a pessimistic evaluation of the act given this partition. The partition is generated sequentially using a greedy algorithm that examines each cell in the partition and only subdivides it further if the split would lead to a sufficiently large refinement of the understanding of the act. Our model can address well-known anomalies related to choice under uncertainty, including Allais-type behavior and violations of non-obvious dominance.

For further information please contact elisur.magrini@unibocconi.it