Abstract for

"Extremely clustered network"

It is now well-known that most real world networks are clustered, i.e. having relatively large clustering coefficient. Motivated by this fact, we optimized a network to have very large clustering coefficient with evolutionary algorithm. Interestingly, we found that optimized network shows scale-free behavior in its degree distribution, another important characteristics of real world network, as well as high clustering coefficient. We show that our model is equivalent to the social network evolution model. As an implementation of this result, we categorize complex networks into two groups: functional and non-functional networks based on their design principles