EAGER: Changing Minds, Changing Probabilities

University Of Kentucky Research Foundation, Lexington KY

Investigators

Abstract

We propose to formalize mathematical models of group decision making that take into account expected behaviors, the effects of exogenous events and influences, and the psychological effects of belief modifications, all in the context of probabilistic reasoning. We are interested in building models sufficient to give us insight into both human and computational preference aggregation and voting processes. For instance, we want to leverage the growing political science work on social networks and voting to build models of voting that reflect complex interpersonal influence between voters. We want to explore work on belief changes in the political science, psychology, and decision sciences literature to include in our models the human tendency to revert to earlier-held beliefs. The intellectual merit of this work lies in the mathematical formalization of theories of group decision making and influence in a stochastic setting; the alignment of such models with those from the political science literature; computational complexity analysis of stochastic models of influence in group decision making, and algorithms for influencing and blocking influence in such settings. This work addresses NSF's third broader impacts category: "Enhance infrastructure for research and education." The field of computational social choice is often said to have begun with Bartholdi, Tovey, and Trick's 1989 paper in the journal Social Choice and Welfare. However, computer scientists were very slow to notice it, and it generated little initial attention in political science. Even now, cooperation and even communication between political and computer scientists about "social choice'" is limited. We will take on the challenging task of interdisciplinary research, attempting to understand problem statements, goals, and results from both bodies of research. We have seen great success by SIGECOM in supporting interdisciplinary work in algorithmic computer science, complexity theory, and economics. We hope to bring that level of interaction to the social choice research areas.