Motivation of Evograph

This web space is aimed at providing a starting place for people who are interested Evolving Graphs with evolutionary algorithms, especially genetic programming. One of the major advantages of genetic programming is its variable length representation making it appropriate to do topologically open-ended synthesis of systems and structures with any kind of graph structures, including
    Structures with homogenous nodes:
            communication networks
            neural networks
            graphs as studied in most graph theory
    Structures with heterogeneous nodes:
            Electric circuits
            Bond graph (widely used in physical system modeling)
            Block diagrams (widely used in control system synthesis)

Although there exist a tremendous stock of research in analyzing graphs in graph theory, some of which may lead to good design strategy for some types of problems, there doesn't exist a generic approach to Synthesize Graphs. Graph Synthesis by Genetic Programming will provide an opportunity to play with how to evolving interesting graphs!

Comment: We are interested here most in Genetic programming, which is a generative approach sharing some similarity to biological developmental process. It is our belief that such an approach is more scalable and more suitable for evolving topologies with heterogeneous nodes. Most interesting structures in physical world belong to this category.