Social network structure and the evolution of cooperation - integrating empirical data and agent-based modelling (#892)
The evolution of cooperation among unrelated individuals is an evolutionary paradox and requires special mechanisms in order to be maintained. Many social species have been found to have non-random social network structures with a high level of clustering. Models have suggested that such non-random network structure can increase the chance that cooperation is maintained in a population. However, these findings have rarely been connected directly to empirical data.
With an integrated approach combining agent-based modelling and empirical data, we investigate the role of social structure for the evolution of cooperation in a classic study system in behavioural ecology, the Trinidadian guppy (Poecilia reticulata). Wild guppies have cooperative partnerships that are used in predator inspection, and the expected level of cooperation in a population thus depends on the predation level.
Using a standard prisoner’s dilemma framework, we develop a computer model simulating the evolution of cooperation in populations with different social network structures. By means of this model and data from natural guppy populations, we investigate whether social networks of wild guppies support cooperation theoretically, and whether the predicted differences in support of cooperation between high and low predation populations are present. We also investigate the role of specific structural and dynamical network features for the maintenance of cooperation in the guppy system. Preliminary simulation results suggest that social network data from highly predated guppies support cooperation, in accordance with expectations. The role of model assumptions for the simulation results will be critically assessed.
With this study we hope to cast new light upon how the direct combination of agent-based modelling and empirical investigations may lead to new insights into the evolution of cooperation.