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  1. Normative Uncertainty and Social Choice.Christian Tarsney - 2019 - Mind 128 (512):1285-1308.
    In ‘Normative Uncertainty as a Voting Problem’, William MacAskill argues that positive credence in ordinal-structured or intertheoretically incomparable normative theories does not prevent an agent from rationally accounting for her normative uncertainties in practical deliberation. Rather, such an agent can aggregate the theories in which she has positive credence by methods borrowed from voting theory—specifically, MacAskill suggests, by a kind of weighted Borda count. The appeal to voting methods opens up a promising new avenue for theories of rational choice under (...)
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  • Utilitarian welfare and representation guarantees of approval-based multiwinner rules.Martin Lackner & Piotr Skowron - 2020 - Artificial Intelligence 288 (C):103366.
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  • The distortion of distributed voting.Aris Filos-Ratsikas, Evi Micha & Alexandros A. Voudouris - 2020 - Artificial Intelligence 286 (C):103343.
  • The distortion of distributed facility location.Aris Filos-Ratsikas, Panagiotis Kanellopoulos, Alexandros A. Voudouris & Rongsen Zhang - 2024 - Artificial Intelligence 328 (C):104066.
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  • The metric distortion of multiwinner voting.Ioannis Caragiannis, Nisarg Shah & Alexandros A. Voudouris - 2022 - Artificial Intelligence 313 (C):103802.
  • Optimizing positional scoring rules for rank aggregation.Ioannis Caragiannis, Xenophon Chatzigeorgiou, George A. Krimpas & Alexandros A. Voudouris - 2019 - Artificial Intelligence 267 (C):58-77.
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  • Primarily about primaries.Allan Borodin, Omer Lev, Nisarg Shah & Tyrone Strangway - 2024 - Artificial Intelligence 329 (C):104095.
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  • The distortion of distributed metric social choice.Elliot Anshelevich, Aris Filos-Ratsikas & Alexandros A. Voudouris - 2022 - Artificial Intelligence 308 (C):103713.
  • Approximating optimal social choice under metric preferences.Elliot Anshelevich, Onkar Bhardwaj, Edith Elkind, John Postl & Piotr Skowron - 2018 - Artificial Intelligence 264 (C):27-51.
  • Peeking behind the ordinal curtain: Improving distortion via cardinal queries.Georgios Amanatidis, Georgios Birmpas, Aris Filos-Ratsikas & Alexandros A. Voudouris - 2021 - Artificial Intelligence 296 (C):103488.
  • Portioning using ordinal preferences: Fairness and efficiency.Stéphane Airiau, Haris Aziz, Ioannis Caragiannis, Justin Kruger, Jérôme Lang & Dominik Peters - 2023 - Artificial Intelligence 314 (C):103809.
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  • Voting methods.Eric Pacuit - 2019 - Stanford Encyclopedia of Philosophy.