Diana Richards, Principal Investigator

Arts: The Probability of Collective Choice with
Shared Mental Models for Large Choice Sets

  Complex decision-making typically involves many agents attempting to aggregate many alternatives. Yet in these large collective choice settings, cyclic outcomes are highly probable, if agents' preferences are unconstraned.

  In previous work, the researchers showed that a knowledge-structure constraint on collective choice overcomes the aggregation paradox for small choice sets. Following this, the researchers expanded on these results to examine the probability of stable collective choice for large choice sets. The results will have implications for cognitive science, where an interpretation of sense data is made by aggregating information from a collective of brain modules; and for social choice, where a group decision is made by aggregating the preferences of a set of individuals.

  Further studies will be performed concerning the probability of stable collective choice for large choice sets when players share a mental model of the choice context, as well as a study of the strategic manipulation of these mental models.