Genetic tuning

It was the latter. It took about 100 generations (each generation with 1000 randomly mutated samples). I didn't take into consideration genetics natures. I thought it would evolve like how we write robots. You know a radar, some basic back and forth movement. Nope, everything spinned, it just happened it stumbled upon a perfect speed and turning ratio to move from its start location (to dodge all walls shots) and a perfect speed to spin its gun and fire to hit walls.

But this was from specific stating positions and angles, which I had programmed into the battle to remove all the extra 'noise' so I could run shorter battles and still get a good sample. Since neither walls or the robots genetics had any random function, I figured it was safe.

After all that work, I decided not to pursue it further. Since it was long boring, and I could write a better robot in 5 minutes.

Preserving the 'noise' is useful in these situations to avoid over-fitting. Although using only Walls in the fitness function will still produce a bot which is only good against it.