A novel paradigm was developed to study the behavior of groups of networked humans searching a problem space. We examined how different network structures affect the diffusion of information about good solutions. Participants made numerical guesses and received scores that were also made available to their neighbors in the network. When the problem space was monotonic and had only one optimal solution, groups were fastest at finding the solution when all of the groups’ information was presented to them. However, when there were good but suboptimal solutions (i.e., local maxima), the group connected via a small-world network (Watts & Strogatz, 1998) was faster at finding the best solution than all other network structures.