2019
AAAI
AAAI 2019
A Better Algorithm for Societal Tradeoffs
Abstract
Abstract 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.
🚀
Conference Pioneer
— AAAI 2019
🌉
Interdisciplinary Bridge
— Computer Science and Mathematics & Optimization
🧭
Keyword Pioneer
— quantitative reasoning
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy