After fixing some minor parameters, the program is basically complete. The neural networks work perfectly as they should given their inputs. Depending on the settings for mutation and elitism, the sweepers will learn to collect the dots in around 5 generations (10 for proficiency) on average. By increasing or decreasing a sweeper's level of fitness depending on it's actions (increasing for hitting a mine) I can change what kind of sweeper will evolve out of the generations. By changing the program so that a sweeper's fitness is decreased when hitting a mine, I can also make them avoid the dots as well. It's amazingly simple to change their behaviors.
The current networks I'm using are incredibly simple, with four inputs, 2 outputs, and a few nodes in between. I'm probably going to do some experimentation on adding different inputs, or changing the game around.
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