Locally noisy autonomous agents improve global human coordination in network experiments

Hirokazu Shirado, Nicholas A. Christakis

Abstract: A networked colour coordination game, with humans interacting with autonomous software bots, shows that bots acting with small levels of random noise and being placed centrally in the network improves not only human–bot interactions but also human–human interactions at distant nodes. Collective action towards a common goal, even if everyone's interests are aligned, faces a 'coordination' problem: an individual's attempts to reach a personal, locally optimized solution may not be optimal for the group as a whole. Now Nicholas Christakis and colleagues have introduced autonomous software ('bots') in small networks of humans engaged in solving a standard colour coordination game in which the collective goal is for every node to have a colour different from all of its neighbour nodes, so as to study the potential benefits of introducing noise in the decision making. They find that noisy bots work best when displaying moderate (10%) randomness and placed centrally in the network. Such bots not only improve human–bot but also human–human interactions at distant nodes, thus helping humans to help themselves. Coordination in groups faces a sub-optimization problem1,2,3,4,5,6 and theory suggests that some randomness may help to achieve global optima7,8,9. Here we performed experiments involving a networked colour coordination game10 in which groups of humans interacted with autonomous software agents (known as bots). Subjects (n = 4,000) were embedded in networks (n = 230) of 20 nodes, to which we sometimes added 3 bots. The bots were programmed with varying levels of behavioural randomness and different geodesic locations. We show that bots acting with small levels of random noise and placed in central locations meaningfully improve the collective performance of human groups, accelerating the median solution time by 55.6%. This is especially the case when the coordination problem is hard. Behavioural randomness worked not only by making the task of humans to whom the bots were connected easier, but also by affecting the gameplay of the humans among themselves and hence creating further cascades of benefit in global coordination in these heterogeneous systems.