Robust mechanisms for information elicitation

Authors:
Aviv Zohar;Jeffrey S. Rosenschein
Affiliations:
The Hebrew University of Jerusalem, Jerusalem, Israel;The Hebrew University of Jerusalem, Jerusalem, Israel
Venue:
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Year:
2006

Citing 1
Cited 2

Robust solutions of uncertain linear programs

Operations Research Letters

Mechanisms for information elicitation

Artificial Intelligence
A Truthful Two-Stage Mechanism for Eliciting Probabilistic Estimates with Unknown Costs

Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

We study information elicitation mechanisms in which a principal agent attempts to elicit the private information of other agents using a carefully selected payment scheme based on proper scoring rules. Scoring rules, like many other mechanisms set in a probabilistic environment, assume that all participating agents share some common belief about the underlying probability of events. In real-life situations however, underlying distributions are not known precisely, and small differences in beliefs about these distributions may alter agent behavior under the prescribed mechanism.We propose designing elicitation mechanisms in a manner that will be robust to small changes in belief. We show how to algorithmically design such mechanisms in polynomial time using tools of stochastic programming and convex programming, and discuss implementation issues for multiagent scenarios.