Preference Elicitation For Participatory Budgeting.

THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE(2021)

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摘要
Participatory budgeting enables the allocation of public funds by collecting and aggregating individual preferences; it has already had a sizable real-world impact. But making the most of this new paradigm requires a rethinking of some of the basics of computational social choice, including the very way in which individuals express their preferences. We analytically compare four preference elicitation methods - knapsack votes, rankings by value or value for money, and threshold approval votes - through the lens of implicit utilitarian voting, and find that threshold approval votes are qualitatively superior. This conclusion is supported by experiments using data from real participatory budgeting elections.
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关键词
group decisions, voting committees, utility preference theory, artificial intelligence
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