Wisdom of the Crowds in Minimum Spanning Tree Problems

Abstract

The „wisdom of the crowds‟ effect describes the finding that combining responses across a number of individuals in a group leads to aggregate performance that is as good as or better than the performance of the best individuals in the group. Here, we look at the wisdom of the crowds effect in the Minimum Spanning Tree Problem (MSTP). The MSTP is an optimization problem where observers must connect a set of nodes into a network with the shortest path length possible. A method is developed that creates aggregate solutions based only on the nodes connected in individuals‟ solutions, without access to spatial information about the nodes. Across the three problems analyzed, the solutions produced by the aggregation method perform better than even the best individual, leading to a strong wisdom of the crowds effect. We show this effect can be observed even with sample sizes as small as 6 individuals.


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