Position-Based Social Choice Methods for Intransitive Incomplete Pairwise Vote Sets (Student Abstract) - Zucker, Julian (Proceedings of the AAAI Conference on Artificial Intelligence, 2020)
Combining the decisions of multiple agents into a final decision requires the use of social choice mechanisms. Pairwise decisions are often incomplete and intransitive, preventing the use of Borda count and other position-based social choice mechanisms. We propose and compare multiple methods for converting incomplete intransitive pairwise vote sets to complete rankings, enabling position-based social choice methods. The algorithms are evaluated on their output’s Kendall’s τ similarity when implementing pairwise social choice mechanisms. We show that there is only a small difference between the outputs of social choice methods on the original pairwise vote set and the generated ranking set on a real-world pairwise voting dataset. Source code for the analysis is available.1