Evolving networks consist of cliques

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Evolving networks by merging cliques.

We propose a model for evolving networks by merging building blocks represented as complete graphs, reminiscent of modules in biological system or communities in sociology. The model shows power-law degree distributions, power-law clustering spectra, and high average clustering coefficients independent of network size. The analytical solutions indicate that a degree exponent is determined by th...

Cliques Role in Organizational Reputational Influence: A Social Network Analysis

Empirical support for the assumption that cliques are major determinants of reputational influence derives largely from the frequent finding that organizations which claimed that their cliques’ connections are influential had an increased likelihood of becoming influential themselves. It is suggested that the strong and consistent connection in cliques is at least partially responsible for the ...

Evolving pseudofractal networks

We present a family of scale-free network model consisting of cliques, which is established by a simple recursive algorithm. We investigate the networks both analytically and numerically. The obtained analytical solutions show that the networks follow a power-law degree distribution, with degree exponent continuously tuned between 2 and 3. The exact expression of clustering coefficient is also ...

Evolving complex networks with conserved clique distributions

We propose and study a hierarchical algorithm to generate graphs having a predetermined distribution of cliques, the fully connected subgraphs. The construction mechanism may be either random or incorporate preferential attachment. We evaluate the statistical properties of the graphs generated, such as the degree distribution and network diameters, and compare them to some real-world graphs.