Running the hard-to-solve maze navigation experiment

As we mentioned, we will use the same experiment runner implementation and the same NEAT hyperparameters settings as in the previous experiment. But we will configure the different maze environment as follows:

$ python -m hard -g 500

After a while, when the experiment is over, we see that even after 500 generations of evolution, a successful maze solver has not been found. The best genome obtained using the neuroevolution algorithm encodes a bizarre and non-functional controller ANN configuration, which is shown in the following diagram:

ANN configuration controlling the ...

Get Hands-On Neuroevolution with Python now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.