Social Learning Over Weakly Connected Graphs

Hawraa Salami · Bicheng Ying · Ali H. Sayed

63 citations0/0 files storedIEEE Transactions on Signal and Information Processing over Networks

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Game Theory and Applications Distributed Control Multi-Agent Systems Opinion Dynamics and Social Influence

Abstract

In this paper, we study diffusion social learning over weakly connected graphs. We show that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations. Under some circumstances that we clarify in this paper, a scenario of total influence (or “mind-control”) arises where a set of influential agents ends up shaping the beliefs of noninfluential agents. We derive useful closed-form expressions that characterize this influence, and which can be used to motivate design problems to control it. We provide simulation examples to illustrate the results.

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References

2010Naïve Learning in Social Networks and the Wisdom of Crowds 2000Pathological Outcomes of Observational Learning 2011Bayesian Learning in Social Networks 2003Rational Herds: Economic Models of Social Learning 2012Non-Bayesian social learning 2010Spread of (mis)information in social networks 2006An Axiomatic Model of Non-Bayesian Updating 2010Non-Bayesian Learning

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