Welfare effects of ex-ante bias and tie-breaking rules on Observational Learning with Fake Agents

Pawan Poojary, Randall Berry

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

Abstract

Networks that provide agents with access to a common database of the agents’ actions enable an agent to easily learn by observing the actions of others, but are also susceptible to manipulation by “fake” agents. Prior work has studied a model for the impact of such fake agents on ordinary (rational) agents in a sequential Bayesian observational learning framework. That model assumes that ordinary agents do not have an ex-ante bias in their actions and that they follow their private information in case of an ex-post tie between actions. This paper builds on that work to study the effect of fake agents on the welfare obtained by ordinary agents under different ex-ante biases and different tie-breaking rules. We show that varying either of these can lead to cases where, unlike in the prior work, the addition of fake agents leads to a gain in welfare. This implies that in such cases, if fake agents are absent or are not adequately present, an altruistic platform could artificially introduce fake actions to effect improved learning.

Original languageEnglish (US)
Title of host publication2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages334-341
Number of pages8
ISBN (Electronic)9783903176553
DOIs
StatePublished - 2023
Event21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023 - Singapore, Singapore
Duration: Aug 24 2023Aug 27 2023

Publication series

NameProceedings of the International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt
ISSN (Print)2690-3334
ISSN (Electronic)2690-3342

Conference

Conference21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023
Country/TerritorySingapore
CitySingapore
Period8/24/238/27/23

Keywords

  • Bayesian optimality
  • ex-ante bias
  • herding
  • Information cascades

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management
  • Control and Optimization
  • Modeling and Simulation

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