DC and VCS

Well, my weighiting them equally idea was only for the movement, for the gun I definitely don't think that will help. (But I'm not sure how much it will hurt.) For VCS movement, each dimension needs to be in a certain range for the gun to use the data from that point. So I would say that each attribute was equally important because the gun needs to match each attribute. (Assuming there was no secondary buffer to go to if there were no matches in a given segment) That being said, because VCS is a binary test, while KNN is a search for the closest point, a normal KNN can't be expected to work exactly like different (but similar) VCS systems. Thinking about it more, it seems like you're right about equal weightings being more complicated than weighitng everything 1.0, but I'm not sure how to deal with that. My initial guess would be weight = 1 / probability_randomly_distributed_situation_in_bin. Which would mean that the weight should be equally to the number of bins used for each attribute.

One problem I have with weighting the distance (or bullet travel time) dimension higher is that, as you said, the distances will mostly be in a range of 400-600. If I were using say one point and I had the option of distance = 450 and velocity change = 0 or distance = 499 and velocity change = 1 with the current situation as distance = 460 and velocity change = 1, the best choice is probably the second point, but weighting the distance higher may favor the first.

I have been wondering for a while how much of Gilgalad's ranking is due to the weighting of KNN and how much is due to a fairly good gun system and wave surfing algorithm, so I am puting a version with all weights (including gun and flattener weights) set to 1.0. (Actually, I forgot to change the weights on the enemy bullet power estimation to 1.0, but I currently only use that for onWin events so it shouldn't make a big difference)