A better algorithm for societal tradeoffs

Conference Paper

In the societal tradeoffs problem, each agent perceives certain quantitative tradeoffs between pairs of activities, and the goal is to aggregate these tradeoffs across agents. This is a problem in social choice; specifically, it is a type of quantitative judgment aggregation problem. A natural rule for this problem was axiomatized by Conitzer et al. [AAAI 2016]; they also provided several algorithms for computing the outcomes of this rule. In this paper, we present a significantly improved algorithm and evaluate it experimentally. Our algorithm is based on a tight connection to minimum-cost flow that we exhibit. We also show that our algorithm cannot be improved without breakthroughs on min-cost flow.

Duke Authors

Cited Authors

  • Zhang, H; Cheng, Y; Conitzer, V

Published Date

  • January 1, 2019

Published In

  • 33rd Aaai Conference on Artificial Intelligence, Aaai 2019, 31st Innovative Applications of Artificial Intelligence Conference, Iaai 2019 and the 9th Aaai Symposium on Educational Advances in Artificial Intelligence, Eaai 2019

Start / End Page

  • 2229 - 2236

International Standard Book Number 13 (ISBN-13)

  • 9781577358091

Citation Source

  • Scopus