Thread:Talk:ScalarBot/Version History/how to build a good test bed?/reply (13)

Movement I find much more interesting - I think there is still a lot of unexplored potential here. Targeting can only get as good as the ML system though. The only tricks I see from targeting side involve bullet shielding and bullet power optimization.

For surfers I evolved the weights in multiple steps - record data, tune weights, re-record data, retune weights etc. I agree fixed data isn't ideal against learning movements, but it seemed to work ok.

By recorded battles, I actually just recorded the ML style interactions. So the only work to do in the genetic algorithm was parse input line, add to tree, and if it was a firing tick then do KNN + kernel density and N ticks later check if the prediction was in the correct bounds.

About 15 minutes per generation for an i5-2410M using 4 threads.