Collective Problem Solving in Networks

Many complex problems in science, business, and engineering require a trade-off between exploitation of known solutions and exploration of new possibilities. When complex problems are solved by collectives rather than individuals, this explore-exploit trade-off is complicated by the presence of communication networks, which can accelerate collective learning, but can also lead to convergence on suboptimal solutions. In this paper, we report on a series of 195 web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. We found that network structure affected collective performance indirectly, via its impact on individual search strategies, as well as directly, by impacting the speed of information diffusion. We also found that networks in general suppress individual exploration, but greatly amplify the benefits of the exploration that takes place. Finally, we identified two ways in which individual and collective performance were in tension, consistent with longstanding theoretical claims.