Hands-On Neuroevolution with Python

Tuning hyperparameters

With proper tuning of the hyperparameters, you can make tremendous improvements in the training speed and efficiency of the neuroevolution process. Here are some practical tips:

• Do short runs with different seed values of the random number generator and note how the algorithm performance changes. After that, choose the seed value that gives the best performance and use it for the long runs.
• You can increase the number of species in the population by decreasing the compatibility threshold and by slightly increasing the value of the disjoint/excess weight coefficient.
• If the process of neuroevolution has stumbled while trying to find a solution, try to decrease the value of the NEAT survival threshold. This coefficient ...