Bayesian decision-makers reaching consensus using expert information

Abstract

The paper is concerned with the problem of Bayesian decision-makers seeking consensus about the decision that should be taken from a decision space. Each decision-maker has his own utility function and it is assumed that the parameter space has two points, Θ = {θ1,θ2 }. The initial probabilities of the decision-makers for Θ can be updated by information provided by an expert. The decision-makers have an opinion about the expert and this opinion is formed by the observation of the expert's performance in the past. It is shown how the decision-makers can decide beforehand, on the basis of this opinion, whether the consultation of an expert will result in consensus.