The value of noise for informational cascades

Tho Ngoc Le, Vijay G. Subramanian, Randall A. Berry

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

6 Scopus citations

Abstract

Informational cascades are said to occur when rational agents ignore their own private information and blindly follow the actions of other agents. Models for such cascades have been well studied for Bayesian agents, who observe perfectly the actions of other agents. In this paper, we investigate the impact of errors in these observations; the errors are modelled via a binary symmetric channel (BSC). Using a Markov chain model, we analyze the net payoff of each agent as a function of his signal quality and the crossover error probability in the channel. Our main result is that a lower error level does not always lead to a higher payoff when the number of agents is large.

Original languageEnglish (US)
Title of host publication2014 IEEE International Symposium on Information Theory, ISIT 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1101-1105
Number of pages5
ISBN (Print)9781479951864
DOIs
StatePublished - 2014
Event2014 IEEE International Symposium on Information Theory, ISIT 2014 - Honolulu, HI, United States
Duration: Jun 29 2014Jul 4 2014

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other2014 IEEE International Symposium on Information Theory, ISIT 2014
CountryUnited States
CityHonolulu, HI
Period6/29/147/4/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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