Incentives for Subjective Evaluations with Private Beliefs
Abstract
The modern web critically depends on aggregation of information from self-interested agents, for example opinion polls, product ratings, or crowdsourcing. We consider a setting where multiple objects (questions, products, tasks) are evaluated by a group of agents. We first construct a minimal peer prediction mechanism that elicits honest evaluations from a homogeneous population of agents with different private beliefs. Second, we show that it is impossible to strictly elicit honest evaluations from a heterogeneous group of agents with different private beliefs. Nevertheless, we provide a modified version of a divergence-based Bayesian Truth Serum that incentivizes agents to report consistently, making truthful reporting a weak equilibrium of the mechanism.
Cite
Text
Radanovic and Faltings. "Incentives for Subjective Evaluations with Private Beliefs." AAAI Conference on Artificial Intelligence, 2015. doi:10.1609/AAAI.V29I1.9311Markdown
[Radanovic and Faltings. "Incentives for Subjective Evaluations with Private Beliefs." AAAI Conference on Artificial Intelligence, 2015.](https://mlanthology.org/aaai/2015/radanovic2015aaai-incentives/) doi:10.1609/AAAI.V29I1.9311BibTeX
@inproceedings{radanovic2015aaai-incentives,
title = {{Incentives for Subjective Evaluations with Private Beliefs}},
author = {Radanovic, Goran and Faltings, Boi},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2015},
pages = {1014-1020},
doi = {10.1609/AAAI.V29I1.9311},
url = {https://mlanthology.org/aaai/2015/radanovic2015aaai-incentives/}
}