Wow, was looking for this (old) challenge! Thank you, MultiplyByZer0.
Regarding the experiment, I know NN has a problem of slow learning since there isn't much data at the beginning of the game. Couldn't a reinforcement of firing waves in the first few rounds solve the problem, though? Another suggestion would be to use waves with low virtuality (those tick waves which are close to a firing tick) to suppress the lack of information without polluting the network with flattening-like data right on the first rounds.
I did something like that in my gun and it improved a lot. Of course, I'm no reference in Neural Targeting: I improved from a really bad gun to a miserable one :) Well, maybe you've already done that after all.
- Thank you MultiplyByZer0. I found out which part of my movement was weak.
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Return to Thread:Talk:Oculus/Movement/reply (30).
- I just looked a little bit more carefully. I found three reasons of getting hit.
- Unknown Wave
- Bot width calculation bug
- Not enough preciseness
- I will fix them all and try again.
Yes I found a bug in bot width calculation.
If there's one thing I learned from Robocode, there are always more bugs. Sometimes the bugs aren't even in the code, but in the assumptions the code was written with. That second category can't be caught with tests, just by looking for deviations from expected behaviour and being smart. The first category can be solved with just a bunch of hard, boring verification work.