neat-python config parameter fitness_criterion on min does not minimize the fitness value

Question

I'm using the neat-python library to find the best neural network that solves a maze. The fitness value is calculated based on the Euclidean distance from my current position to the exit. Ideally, the best fitness value would be 0. To achieve this, I set the fitness_criterion to "min". However, I'm experiencing an issue where the run method terminates after a single generation with the highest fitness value. I'm wondering if there are any other configurations that need to be adjusted in my code, rather than just in the config file.