Social Learning Equilibria
We consider social learning settings in which a group of agents face uncertainty regarding a state of the world, observe private signals, share the same utility function, and act in a general dynamic setting. We introduce Social Learning Equilibria, a static equilibrium concept that abstracts away f...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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ACM
2020
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| Online Access: | https://hdl.handle.net/1721.1/125593 |
| _version_ | 1811098215302299648 |
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| author | Mossel, Elchanan Mueller-Frank, Manuel Sly, Allan Tamuz, Omer |
| author2 | Massachusetts Institute of Technology. Department of Mathematics |
| author_facet | Massachusetts Institute of Technology. Department of Mathematics Mossel, Elchanan Mueller-Frank, Manuel Sly, Allan Tamuz, Omer |
| author_sort | Mossel, Elchanan |
| collection | MIT |
| description | We consider social learning settings in which a group of agents face uncertainty regarding a state of the world, observe private signals, share the same utility function, and act in a general dynamic setting. We introduce Social Learning Equilibria, a static equilibrium concept that abstracts away from the details of the given dynamics, but nevertheless captures the corresponding asymptotic equilibrium behavior. We establish strong equilibrium properties on agreement, herding, and information aggregation. Keywords: Consensus; Information Aggregation; Herding |
| first_indexed | 2024-09-23T17:11:43Z |
| format | Article |
| id | mit-1721.1/125593 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T17:11:43Z |
| publishDate | 2020 |
| publisher | ACM |
| record_format | dspace |
| spelling | mit-1721.1/1255932022-10-03T11:04:20Z Social Learning Equilibria Mossel, Elchanan Mueller-Frank, Manuel Sly, Allan Tamuz, Omer Massachusetts Institute of Technology. Department of Mathematics We consider social learning settings in which a group of agents face uncertainty regarding a state of the world, observe private signals, share the same utility function, and act in a general dynamic setting. We introduce Social Learning Equilibria, a static equilibrium concept that abstracts away from the details of the given dynamics, but nevertheless captures the corresponding asymptotic equilibrium behavior. We establish strong equilibrium properties on agreement, herding, and information aggregation. Keywords: Consensus; Information Aggregation; Herding 2020-06-01T13:55:46Z 2020-06-01T13:55:46Z 2019-10 2019-11-18T12:52:34Z Article http://purl.org/eprint/type/ConferencePaper 9781450358293 https://hdl.handle.net/1721.1/125593 Mossel, Elchanan et al., "Social Learning Equilibria." EC '18: Proceedings of the 2018 ACM Conference on Economics and Computation (EC), June 2018, Ithaca NY, Association for Computing Machinery, 2019 en https://dx.doi.org/10.1145/3219166.3219207 Proceedings of the 2018 ACM Conference on Economics and Computation Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf ACM arXiv |
| spellingShingle | Mossel, Elchanan Mueller-Frank, Manuel Sly, Allan Tamuz, Omer Social Learning Equilibria |
| title | Social Learning Equilibria |
| title_full | Social Learning Equilibria |
| title_fullStr | Social Learning Equilibria |
| title_full_unstemmed | Social Learning Equilibria |
| title_short | Social Learning Equilibria |
| title_sort | social learning equilibria |
| url | https://hdl.handle.net/1721.1/125593 |
| work_keys_str_mv | AT mosselelchanan sociallearningequilibria AT muellerfrankmanuel sociallearningequilibria AT slyallan sociallearningequilibria AT tamuzomer sociallearningequilibria |