2024
IJCAI
IJCAI 2024
Aggregation of Continuous Preferences in One Dimension
Abstract
We develop a general, formal model of social choice in which voters have continuous preferences over a one-dimensional space. Our model is parameterized by different restrictions that we introduce regarding the way voter preferences change in time as well as the optimization criteria (that correspond to a normative continuum of fairness definitions) desired from an aggregation method---that outputs a continuous, one-dimensional curve---given such inputs. We discuss the applicability of the model to different real-world situations and, as a first step towards an analysis of the different model realizations, we concentrate on identifying those cases that are computationally feasible to compute.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning
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Keyword Pioneer
— normative fairness
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy