The HyperNEAT method, which we discussed in Chapter 7, Hypercube-Based NEAT for Visual Discrimination, allows us to use neuroevolution methods for a broad class of problems that require the use of large-scale ANN structures to find a solution. This class of problem spreads across multiple practical domains, including visual pattern recognition. The main distinguishing feature of all these problems is the high dimensionality of the input/output data.
In the previous chapter, you learned how to define the configuration of the substrate of the discriminator ANN to solve a visual discrimination task. You also learned that it is crucial to use an appropriate substrate configuration that is aligned with the geometric features of the search space of the target problem. With the HyperNEAT method, you, as an...
