Hands-On Neuroevolution with Python

XOR problem basics

The classic multilayer perceptron (MLP) or artificial neural network (ANN) without any hidden units in their topology is only capable of solving linearly separable problems correctly. As a result, such ANN configurations cannot be used for pattern recognition or control and optxor_experiment.pyimization tasks. However, with more complex MLP architectures that include some hidden units with a kind of non-linear activation function (such as sigmoid), it is possible to approximate any function to the given accuracy. Thus, a non-linearly separable problem can be used to study whether a neuroevolution process can grow any number of hidden units in the ANN of the solver phenotype.

The XOR problem solver is a classic computer ...