  Models of continuous opinion dynamics under bounded confidence show a sharp
transition between a consensus and a polarization phase at a critical global
bound of confidence. In this paper, heterogeneous bounds of confidence are
studied. The surprising result is that a society of agents with two different
bounds of confidence (open-minded and closed-minded agents) can find consensus
even when both bounds of confidence are significantly below the critical bound
of confidence of a homogeneous society.
  The phenomenon is shown by examples of agent-based simulation and by
numerical computation of the time evolution of the agents density. The result
holds for the bounded confidence model of Deffuant, Weisbuch and others
(Weisbuch, G. et al; Meet, discuss, and segregate!, Complexity, 2002, 7,
55--63), as well as for the model of Hegselmann and Krause (Hegselmann, R.,
Krause, U.; Opinion Dynamics and Bounded Confidence, Models, Analysis and
Simulation, Journal of Artificial Societies and Social Simulation, 2002, 5, 2).
  Thus, given an average level of confidence, diversity of bounds of confidence
enhances the chances for consensus. The drawback of this enhancement is that
opinion dynamics becomes suspect to severe drifts of clusters, where
open-minded agents can pull closed-minded agents towards another cluster of
closed-minded agents. A final consensus might thus not lie in the center of the
opinion interval as it happens for uniform initial opinion distributions under
homogeneous bounds of confidence. It can be located at extremal locations. This
is demonstrated by example.
  This also show that the extension to heterogeneous bounds of confidence
enriches the complexity of the dynamics tremendously.
