Condorcet Markets
Fuente:
arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866910524451586048 |
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| author | Airiau, Stéphane Dupuis, Nicholas Kees Grossi, Davide |
| author_facet | Airiau, Stéphane Dupuis, Nicholas Kees Grossi, Davide |
| contents | The paper studies information markets concerning single events from an epistemic social choice perspective. Within the classical Condorcet error model for collective binary decisions, we establish equivalence results between elections and markets, showing that the alternative that would be selected by weighted majority voting (under specific weighting schemes) corresponds to the alternative with highest price in the equilibrium of the market (under specific assumptions on the market type). This makes it possible in principle to implement specific weighted majority elections, which are known to have superior truth-tracking performance, by means of information markets without needing to elicit voters' competences. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_05028 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Condorcet Markets Airiau, Stéphane Dupuis, Nicholas Kees Grossi, Davide Computer Science and Game Theory Multiagent Systems The paper studies information markets concerning single events from an epistemic social choice perspective. Within the classical Condorcet error model for collective binary decisions, we establish equivalence results between elections and markets, showing that the alternative that would be selected by weighted majority voting (under specific weighting schemes) corresponds to the alternative with highest price in the equilibrium of the market (under specific assumptions on the market type). This makes it possible in principle to implement specific weighted majority elections, which are known to have superior truth-tracking performance, by means of information markets without needing to elicit voters' competences. |
| title | Condorcet Markets |
| topic | Computer Science and Game Theory Multiagent Systems |
| url | https://arxiv.org/abs/2306.05028 |