  In the consensus model of Sznajd, opinions are integers and a randomly chosen
pair of neighbouring agents with the same opinion forces all their neighbours
to share that opinion. We propose a simple extension of the model to continuous
opinions, based on the criterion of bounded confidence which is at the basis of
other popular consensus models. Here the opinion s is a real number between 0
and 1, and a parameter \epsilon is introduced such that two agents are
compatible if their opinions differ from each other by less than \epsilon. If
two neighbouring agents are compatible, they take the mean s_m of their
opinions and try to impose this value to their neighbours. We find that if all
neighbours take the average opinion s_m the system reaches complete consensus
for any value of the confidence bound \epsilon. We propose as well a weaker
prescription for the dynamics and discuss the corresponding results.

Statistical Mechanics;Disordered Systems and Neural Networks