ML Anthology

An Incentive Mechanism for Promoting Honesty in E-Marketplaces

Jie Zhang
AAAI 2007 pp. 1957-1958
/aaai/2007/zhang2007aaai-incentive/

Abstract

Problem to be Addressed Our research is within the subfield of modeling trust and reputation in multi-agent systems for electronic commerce. More specifically, we are interested in addressing two prob-lems that may arise in trust and reputation models where buying agents elicit opinions about selling agents from other buyers (known as advisors) in the marketplace: • Unfair ratings of sellers provided to buyers • Developing incentives for buyers to report their ratings of sellers To explain, the ratings provided by advisors are possibly un-fair. Buyers may provide unfairly high ratings to promote the seller. This is referred to as “ballot stuffing ” (Dellaro-cas 2000). Buyers may also provide unfairly low ratings, in order to cooperate with other sellers to drive a seller out

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Text

Zhang. "An Incentive Mechanism for Promoting Honesty in E-Marketplaces." AAAI Conference on Artificial Intelligence, 2007.

Markdown

[Zhang. "An Incentive Mechanism for Promoting Honesty in E-Marketplaces." AAAI Conference on Artificial Intelligence, 2007.](https://mlanthology.org/aaai/2007/zhang2007aaai-incentive/)

BibTeX

@inproceedings{zhang2007aaai-incentive,
  title     = {{An Incentive Mechanism for Promoting Honesty in E-Marketplaces}},
  author    = {Zhang, Jie},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2007},
  pages     = {1957-1958},
  url       = {https://mlanthology.org/aaai/2007/zhang2007aaai-incentive/}
}