Policies for allocation of information in task-oriented groups: elitism and egalitarianism outperform welfarism

Communication is probably the most controllable factor that are known to impact on the problem-solving capability of task-forces. In the case connections are costly, it is nedeed a better policy to allocate them to the individuals. We use an agent-based model to study how distinct allocation policies affect the performance of a group of agents whose task is to find the global maxima of NK fitness landscapes. The larger the influence neighborhood of an agent, more information it receives. We find that the elitist policy in which agents with above-average fitness have their influence neighborhoods amplified is optimal for smooth landscapes, provided the group size is not too small. For rugged landscapes, however, the elitist policy can perform very poorly for certain group sizes. In addition, we find that the egalitarian policy, in which the size of the influence neighborhood is the same for all agents, is optimal for both smooth and rugged landscapes in the case of small groups. The welfarist policy, in which the actions of the elitist policy are reversed, is always suboptimal, i.e., depending on the group size it is outperformed by either the elitist or the egalitarian policies.
Reia et al, Eur. Phys. J. B (2019) 92: 205. DOI: https://doi.org/10.1140/epjb/e2019-100345-7.