Zusammenfassung
We use agent-based modeling to investigate the effect of conservatism
and partisanship on the efficiency with which large populations solve
the density classification task - a paradigmatic problem for information
aggregation and consensus building. We find that conservative agents
enhance the populations' ability to efficiently solve the density
classification task despite large levels of noise in the system. In
contrast, we find that the presence of even a small fraction of
partisans holding the minority position will result in deadlock or a
consensus on an incorrect answer. Our results provide a possible
explanation for the emergence of conservatism and suggest that even low
levels of partisanship can lead to significant social costs.
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