Establishing social cooperation: the role of hubs and community structure

Prisoner’s Dilemma games have become a well-established paradigm for studying the mechanisms by which cooperative behaviour may evolve in societies consisting of selfish individuals. Recent research has focussed on the effect of spatial and connectivity structure in promoting the emergence of cooperation in scenarios where individuals play games with their neighbors, using simple ‘memoryless’ rules to decide their choice of strategy in repeated games. While heterogeneity and structural features such as clustering have been seen to lead to reasonable levels of cooperation in very restricted settings, no conditions on network structure have been established which robustly ensure the emergence of cooperation in a manner which is not overly sensitive to parameters such as network size, average degree, or the initial proportion of cooperating individuals. Here we consider a natural random network model, with parameters which allow us to vary the level of ‘community’ structure in the network, as well as the number of high degree hub nodes. We investigate the effect of varying these structural features and show that, for appropriate choices of these parameters, cooperative behaviour does now emerge in a truly robust fashion and to a previously unprecedented degree. The implication is that cooperation (as modelled here by Prisoner’s Dilemma games) can become the social norm in societal structures divided into smaller communities, and in which hub nodes provide the majority of inter-community connections

The idemetric property: when most distances are (almost) the same

We introduce the idemetric property, which formalizes the idea that most nodes in a graph have similar distances between them, and which turns out to be quite standard amongst small-world network models. Modulo reasonable sparsity assumptions, we are then able to show that a strong form of idemetricity is actually equivalent to a very weak expander condition (PUMP). This provides a direct way of providing short proofs that small-world network models such as the Watts-Strogatz model are strongly idemetric (for a wide range of parameters), and also provides further evidence that being idemetric is a common property. We then consider how satisfaction of the idemetric property is relevant to algorithm design. For idemetric graphs, we observe, for example, that a single breadth-first search provides a solution to the all-pairs shortest paths problem, so long as one is prepared to accept paths which are of stretch close to 2 with high probability. Since we are able to show that Kleinberg's model is idemetric, these results contrast nicely with the well known negative results of Kleinberg concerning efficient decentralized algorithms for finding short paths: for precisely the same model as Kleinberg's negative results hold, we are able to show that very efficient (and decentralized) algorithms exist if one allows for reasonable preprocessing. For deterministic distributed routing algorithms we are also able to obtain results proving that less routing information is required for idemetric graphs than in the worst case in order to achieve stretch less than 3 with high probability: while Ω(n 2) routing information is required in the worst case for stretch strictly less than 3 on almost all pairs, for idemetric graphs the total routing information required is O(nlog(n))