Doing better against simple targeters

Fragment of a discussion from Talk:Movement
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But since simple guns are pretry predictable, you can always crush them by preloading gfs.

Xor (talk)12:52, 6 October 2017

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.

Rsalesc (talk)12:55, 6 October 2017

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

Xor (talk)13:11, 6 October 2017
 

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).

Xor (talk)15:29, 6 October 2017

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

Dsekercioglu (talk)15:35, 6 October 2017

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.

Xor (talk)17:23, 6 October 2017

What is a probability view?

Dsekercioglu (talk)19:54, 6 October 2017

meaning traditional wave surfing buffers

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

Xor (talk)21:23, 6 October 2017
 
 
 
 

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.

Dsekercioglu (talk)15:38, 6 October 2017