Social Learning Equilibria
Name
1207.5895.pdf
Description
Accepted version
Size
425.54 KB
Format
Adobe PDF
Checksum (MD5)
945020da6e1d938ff15e5024bea00858
Author(s)
Mossel, Elchanan
Mueller-Frank, Manuel
Sly, Allan
Tamuz, Omer
Date Issued
October 2019
Journal
Proceedings of the 2018 ACM Conference on Economics and Computation
Publisher
ACM
Citation
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
Version
Author's final manuscript
Abstract
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
MIT Department
Massachusetts Institute of Technology. Department of Mathematics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3219166.3219207
