In this chapter, we learned about the neuroevolution method that allows the substrate configuration to evolve during the process of finding the solution to the problem. This approach frees the human designer from the burden of creating a suitable substrate configuration to the smallest details, allowing us to define only the primary outlines. The algorithm will automatically learn the remaining details of the substrate configuration during the evolution.
Also, you learned about the modular ANN structures that can be used to solve various problems, including the modular retina problem. Modular ANN topologies are a very powerful concept that allows the reuse of the successful phenotype ANN module multiple times to build a complex hierarchical topology. Furthermore, you have had the chance to hone your skills with the Python programming language by implementing the corresponding...
