Abstract:
We study the societal tradeoffs problem, where a set of voters each submit their ideal tradeoff value between each pair of activities (e.g., "using a gallon of gasoline is as bad as creating 2 bags of landfill trash"), and these are then aggregated into the societal tradeoff vector using a rule. We introduce the family of distance-based rules and show that these can be justified as maximum likelihood estimators of the truth. Within this family, we single out the logarithmic distance-based rule as especially appealing based on a social-choice-theoretic axiomatization. We give an efficient algorithm for executing this rule as well as an approximate hill climbing algorithm, and evaluate these experimentally.
DOI:
10.1609/aaai.v30i1.10055