How to trust a few among many

Anthony Etuk, Timothy J. Norman, Murat Sensoy, Mudhakar Srivasta

Research output: Contribution to journalArticle

1 Citation (Scopus)
4 Downloads (Pure)

Abstract

The presence of numerous and disparate information sources available to support decision-making calls for efficient methods of harnessing their potential. Information sources may be unreliable, and misleading reports can affect decisions. Existing trust and reputation mechanisms typically rely on reports from as many sources as possible to mitigate the influence of misleading reports on decisions. In the real world, however, it is often the case that querying information sources can be costly in terms of energy, bandwidth, delay overheads, and other constraints. We present a model of source selection and fusion in resource-constrained environments, where there is uncertainty regarding the trustworthiness of sources. We exploit diversity among sources to stratify them into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of certain biases. Through controlled experiments, we demonstrate that a diversity-based approach is robust to biases introduced due to dependencies among source reports, performs significantly better than existing approaches when sampling budget is limited and equally as good with an unlimited budget.
Original languageEnglish
Pages (from-to)531-560
Number of pages30
JournalAutonomous Agents and Multi-Agent Systems
Volume31
Issue number3
Early online date25 May 2016
DOIs
Publication statusPublished - May 2017

Keywords

  • trust
  • reputation
  • diversity
  • sampling

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  • Cite this

    Etuk, A., Norman, T. J., Sensoy, M., & Srivasta, M. (2017). How to trust a few among many. Autonomous Agents and Multi-Agent Systems, 31(3), 531-560. https://doi.org/10.1007/s10458-016-9337-5