The problem of detecting community structure in complex networks received quite a bit of attention in recent years, probably since it is not only theoretically important, but also highly relevant to practical applications. Therefore, a wide range of tools have been applied to this domain, including both more traditional machine learning methods, and various types of evolutionary algorithms. In this tutorial we will not only dive into some of the fascinating methods employed in this highly active field, but also compare them in various ways, using several different yardsticks. On top of that, we will attempting to answer the question: have evolutionary methods proven their worth in this complex domain, or is it currently better to rely on standard clustering methods?
Evolutionary computation methods e-session
Photos by : ASA Goddard Space Flight Center