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Liar liar, pants on fire; or how to use subjective logic and argumentation to evaluate information from untrustworthy sources

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Abstract

This paper presents a non-prioritized belief change operator, designed specifically for incorporating new information from many heterogeneous sources in an uncertain environment. We take into account that sources may be untrustworthy and provide a principled method for dealing with the reception of contradictory information. We specify a novel Data-Oriented Belief Revision Operator, that uses a trust model, subjective logic, and a preference-based argumentation framework to evaluate novel information and change the agent’s belief set accordingly. We apply this belief change operator in a collaborative traffic scenario, where we show that (1) some form of trust-based non-prioritized belief change operator is necessary, and (2) in a direct comparison between our operator and a previous proposition, our operator performs at least as well in all scenarios, and significantly better in some.

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Notes

  1. The ODD protocol was designed to standardize the method for describing Agent-Based Models in order to facilitate understanding and duplication, and thus solves a number of the problems existing in simply sharing a code base.

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Authors and Affiliations

  1. http://www.andrewkoster.net

    Andrew Koster

  2. Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil

    Ana L. C. Bazzan

  3. Santa Catarina State University, Ibirama, SC, Brazil

    Marcelo de Souza

Authors
  1. Andrew Koster
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  2. Ana L. C. Bazzan
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  3. Marcelo de Souza
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Correspondence to Andrew Koster.

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Koster, A., Bazzan, A.L.C. & de Souza, M. Liar liar, pants on fire; or how to use subjective logic and argumentation to evaluate information from untrustworthy sources. Artif Intell Rev 48, 219–235 (2017). https://doi.org/10.1007/s10462-016-9499-1

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