Social learning with decentralized choice of private signals

Christophe Chamley, Anna Scaglione

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Social learning is analyzed when agents choose the type of information in a set of signals to identify the state of a fundamental variable. It is shown that agents may herd on the type of signal that is chosen and herding is socially inefficient. The public reports of agents may have to be restricted to improve the efficiency of social learning. As an example of application, the mechanism is relevant for warnings against a particular threat.

Original languageEnglish (US)
Title of host publication2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
Pages547-550
Number of pages4
DOIs
StatePublished - Dec 1 2013
Externally publishedYes
Event2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Austin, TX, United States
Duration: Dec 3 2013Dec 5 2013

Publication series

Name2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

Other

Other2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013
CountryUnited States
CityAustin, TX
Period12/3/1312/5/13

Keywords

  • Decentralized learning
  • Social networks

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Cite this

Chamley, C., & Scaglione, A. (2013). Social learning with decentralized choice of private signals. In 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings (pp. 547-550). [6736936] (2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings). https://doi.org/10.1109/GlobalSIP.2013.6736936