Robust Non-Bayesian Social Learning

Segev Shlomov
Segev Shlomov

Proceedings of the 2019 ACM Conference on Economics and Computation, pp. 549-550, 2019.

Cited by: 0|Bibtex|Views5|DOI:https://doi.org/10.1145/3328526.3329588
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

We study non-Bayesian social learning in large networks and binary state space. Agents who are located in a network receive conditionally i.i.d. signals over the state. We refer to the initial distribution of signals as the information structure. In each step, all agents aggregate their belief with the beliefs of their neighbors according...More

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