Feasible Conditional Belief Distributions
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866916483888578560 |
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| author | Arieli, Itai Babichenko, Yakov Sandomirskiy, Fedor |
| author_facet | Arieli, Itai Babichenko, Yakov Sandomirskiy, Fedor |
| contents | Agents receive private signals about an unknown state. The resulting joint belief distributions are complex and lack a simple characterization. Our key insight is that, when conditioned on the state, the structure of belief distributions simplifies: feasibility constrains only the marginal distributions of individual agents across states, with no joint constraints within a state. We apply this insight to multi-receiver persuasion, identifying new tractable cases and introducing optimal transportation and duality tools. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2307_07672 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Feasible Conditional Belief Distributions Arieli, Itai Babichenko, Yakov Sandomirskiy, Fedor Theoretical Economics Computer Science and Game Theory Agents receive private signals about an unknown state. The resulting joint belief distributions are complex and lack a simple characterization. Our key insight is that, when conditioned on the state, the structure of belief distributions simplifies: feasibility constrains only the marginal distributions of individual agents across states, with no joint constraints within a state. We apply this insight to multi-receiver persuasion, identifying new tractable cases and introducing optimal transportation and duality tools. |
| title | Feasible Conditional Belief Distributions |
| topic | Theoretical Economics Computer Science and Game Theory |
| url | https://arxiv.org/abs/2307.07672 |