Doing better against simple targeters

Can you run your bot against those three when you have time? Just for the sake of my curiosity :P

ScalarBot is doing very bad against wsc LT/CT, but my score against those bots in real world seems to be even higher than some top bots. Seems that my gun is destroying them before they even had a chance to shot. ;)

I tried some dedicated buffer for the simple targeters, but it just don’t work (not giving me more score).

I think that’s because I’m too far away, visiting every fire situation, and making simple guns fire at every possible gf.

That is probably because bots using "Fast Targeting" also use some non-learning movement.

But since simple guns are pretry predictable, you can always crush them by preloading gfs.

Yes, I do that, but I eventually start getting hit and then I stop falling back to my preloaded GFs. What I wonder is how those top 2K6 bots can still learn well.

well, don’t use one hit as some threshold, rather, do that smoother

Another trick I think is that to use very large bandwidth, since WscB & C will fire at near 1.0 when you have some speed, being as far as possible helps a lot.

Since ScalarBot is using something more like uniform shape function (and very low weighted 1 / (1 + sq(x)) to hint true surfing), and it's weighting secondary wave equally for same bullet power, without evaluating stationary danger, all making it visit as much gfs as possible, it's not strange it will perform very bad against simple guns (where being precise and strict hurts).

Maybe trying Normal Distribution would help. Sometimes I see Rechner just going between 2 possible bullet locations and get hit there.

I am using normal distribution in probability view. But this is not helping me against simple guns.

iirc something like 1 / (1 + abs(x)) works better.

What is a probability view?

meaning traditional wave surfing buffers

as my style is more like shrapnel surfing, which is called peak views.

I know bots starts using new predictors when enemy hit rate increases. It is just like a flattener but still does hit learning. Also I am amazed by Dookious and DrussGT dodging every type of targeting near perfect.

Wow, it seem that SimpleBot is performing way better —

| SimpleBot 0.024c.c.mc || Author || Type || 99.42 || 95.18 || 94.67 || 96.42 || 100.0 seasons

Where the biggest difference is the lack of precise intersection, and the use of 1 / (1 + abs(x)) as danger function.

Also, SimpleBot is examing stationary danger in both waves.