why virtual waves help

So, I am wondering why virtual waves help. I think the reason is that many robots make a movement decision every turn, rather than every shot. Excluding that as a reason, as far as I can see, the reasoning behind them would be: "My enemy needs to move at least when I shoot. The GFs he ends up at while moving are related to the final GF. So training based on the intermediate GFs will approximate the final GF." My problems with these reasons are a) I don't like making my gun better for what happens to be common (making a decision about movement every turn) rather than about what should be common. b) I don't want to approximate the final GF, I want to use it exactly.

Am I missing anything about virtual waves that would explain why they are a good idea?

My current plan is to remove them, and then, since my data set will be about 15 times smaller, I could add 5 or so new dimensions like "average turn rate in the past 10 turns", etc. that would hopefully make up for the lost data.

Even for surfers, lots of decisions are the same no matter what you're doing in terms of bullet dodging, things like dive protection and adjusting distancing. I think it's a good idea to experiment, but I'm willing to bet you'll find the 15x bigger data set is worth it. :-) And couldn't you afford a few extra attributes regardless? I know my gun is plenty fast for however many attributes I want, if I found any new ones to be worthwhile, which I haven't.

I have my main gun, which uses virtual waves, and my anti-surfer gun, which doesn't. The problem with not using virtual waves is that you don't start learning their movement patterns until you spend energy, so at the beginning it will not be very accurate. I've considered using virtual waves until my actual waves have enough data, then dropping the virtual waves, but I'm not sure it would help that much.

I'd phrase it as being a tradeoff between "small data set with no bias" versus "big data set with bias". Unless the enemy robot is intentionally creating the bias, the big data set pretty much always worth it. Even when the enemy robot is intentionally creating a bias, it's not always a big enough bias to outweigh the benefit of the larger data set.

I don't think the "small data set with no bias" vs "large data set with bias" is quite correct though. If it were 15 times more unique situations with some bias thrown in I would think you would be right, but these are all related to the unbiased situations, so we have more of a "data set with more details and bias" rather than just a larger data set. Of course, I do lose a significant amount on the TCRM by removing it.

Eh, the gaps in time between bullet waves are kind of huge really. "15x larger data set" would be an overstatement due to the redundant data of strongly correlated data points, but I'd still characterise it as a larger data set by some magnitude, due to how large the large gaps between bullet waves are.