Almost always, proper visualization of inputs and results is crucial to the success of your experiment. With proper visualization, you will get intuitive insights about what has gone wrong and what needs to be fixed.
Always try to visualize the simulator execution environment. Such visualization can save you hours of debugging when you get an unexpected result. Usually, with adequate visualization, you can see that something has gone wrong at a glance, such as a maze solver that got stuck up in a corner.
With neuroevolution algorithms, you also need to visualize the performance of the genetic algorithm execution per generation. You need to visualize speciation from generation to generation to see whether the evolutionary process has stagnated. Stagnated evolution fails to create enough species to maintain healthy diversity among solvers. On the other hand...
