Event Detail

The problem of how to aggregate the conflicting preferences of multiple agents into a group decision has occupied social choice theorists since at least the 18th century. In tackling this problem today, we have the benefit of not only modern mathematical techniques but also tools from computer science. In this talk, I will survey some of my recent work on ordinal preference aggregation, which leverages interactive theorem proving, SAT solving, Monte Carlo simulations, and machine learning. We have obtained not only a better understanding of the landscape of preferential voting methods but also arguments for specific methods: the Split Cycle method and its later refinement, Stable Voting, implemented at https://stablevoting.org/. In addition to introducing these methods, I will pose some open problems, including problems about computational complexity.