Don't Believe Everything You Hear: Preserving Relevant Information by Discarding Social Information

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Integrating information gained by observing others via Social Bayesian Learning can be beneficial for an agent’s performance, but can also enable population wide information cascades that perpetuate false beliefs through the agent population.
We show how agents can influence the observation network by changing their probability of observing others, and demonstrate the existence of a population-wide equilibrium, where the advantages and disadvantages of the Social
Bayesian update are balanced. We also use the formalism of relevant information to illustrate how negative information cascades are characterized by processing increasing amounts of non-relevant information
Original languageEnglish
Title of host publicationALIFE 14
Subtitle of host publicationProcs of the 14th Int Conf on the Synthesis and Simulation of Living Systems
PublisherMIT Press
Number of pages8
Publication statusPublished - 2014
EventALIFE 2014 - New York, United States
Duration: 30 Jul 20142 Aug 2014


ConferenceALIFE 2014
Country/TerritoryUnited States
CityNew York

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