Smuggler Archive
Thread: Theory of slicing results and probabilities
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SpinningCloud
Fri Mar 04, 2005 2:49 pm
#1
Normally an RNG routine call takes a range and returns a value within that range with a distribution at the center of the range. If you ask for an integer between 15 and 35 then it will return a pseudo random number in that range.
RNGs come in varieties for C++ that will generate floating point and integer numbers with uniform or nonuniform distributions. The nonuniform distributions can be of normal, bernoulli, poisson, binomial, hypergeometric, noncentral hypergeometric, multinomial, ultivariate hypergeometric, noncentral hypergeometric and shuffling.
Why would they code something special when a simple standard function call with the variety offered by C++ RNG functions would suffice?
Message Edited by SpinningCloud on 03-04-2005 01:54 PM
zChuckRoastz
Fri Mar 04, 2005 2:51 pm
#2
maxtheusher wrote:
d00dz but sl1c1ng 1sn'T r4ndumb, j00 jUst h4v 2 34t t\/\/1zzl3rz wh1l3 s1ng1ng b4b33 g0t b4ck!!!11!!!!oneone!!
Damn, I understand that jibberish and I'm old.
Dark_0ne
Fri Mar 04, 2005 4:19 pm
#4
yeah - with one exception .....
when slicing PSGs, 9 times out of 10 you will get an encumbrance slice (or at least I will !!!)
I sliced 32 of them this evening and 25 were encumbrance and the rest were mostly 15 - 20 % effectiveness with a couple at about 30% effectiveness !!!!
was I annoyed ?
when slicing PSGs, 9 times out of 10 you will get an encumbrance slice (or at least I will !!!)
I sliced 32 of them this evening and 25 were encumbrance and the rest were mostly 15 - 20 % effectiveness with a couple at about 30% effectiveness !!!!
was I annoyed ?
SpinningCloud
Fri Mar 04, 2005 8:14 pm
#5
you think this theory is right?
Please read my post about RNG functions in programming...
Subcribe to the KISS principle, life will be easier and more predictable.
Mackle
Fri Mar 04, 2005 10:45 pm
#6
Bermag, you are confusing me. It's way too early/late to be doing that kind of math.
I do know that I need a new Geo Pistol, though.
I do know that I need a new Geo Pistol, though.
Bermag
Sat Mar 05, 2005 1:08 am
#7
On my way home form work today I started to think about the probabilities for various slices. I remembered a post in this forum that showed it to be randomly distributed but however weighted with a higher frequency of mid range slices. I started to think about probability theory and if there is a higher frequency on some slicing% then it could not be one random roll becuase in that case there should be just as many 35% slices as there are 25% slices.
So I come to the conclusion that it must be two random rolls added together. This create a bell shaped distribution of slice results. Just as you throw two dices the most common result is 7, becuase there are more combination of 7 on a six side dice than other choices.
At least with weapons I think it is like this:
Slicing result is 15% + random roll 0-10 + random roll 0-10
Might be other combinations but I could not get the numbers correct (and starting at 0 is common in programming).
This means that there are 11x11=121 possible combinations. If you want to see the possible outcomes then make a grid with numbers 0-10 and you will see the possible combination. The result of frequncies is a triangle form "curve".
To get a 35% (or 15%) there is only one possible combination so the probability to get a 35% slice is 1/121 = 0.8%
The most probable outcome is 25% which is 11/121= 9%
To get 30% or better the probability is 21/121.
However, it get worse :-). There is also a roll if it is speed slice or damage slice which is 50% probability. So if you are looking for that 35% damage slice the probability is 50% of 1/21= 1/242 = 0.4%
With other words 1 out of 242 slices is a 35% damage slice.
I am not 100% sure about the math, I might be wrong. Please comment. I am a bit surprised that the probability for 35% is that low.
So I come to the conclusion that it must be two random rolls added together. This create a bell shaped distribution of slice results. Just as you throw two dices the most common result is 7, becuase there are more combination of 7 on a six side dice than other choices.
At least with weapons I think it is like this:
Slicing result is 15% + random roll 0-10 + random roll 0-10
Might be other combinations but I could not get the numbers correct (and starting at 0 is common in programming).
This means that there are 11x11=121 possible combinations. If you want to see the possible outcomes then make a grid with numbers 0-10 and you will see the possible combination. The result of frequncies is a triangle form "curve".
To get a 35% (or 15%) there is only one possible combination so the probability to get a 35% slice is 1/121 = 0.8%
The most probable outcome is 25% which is 11/121= 9%
To get 30% or better the probability is 21/121.
However, it get worse :-). There is also a roll if it is speed slice or damage slice which is 50% probability. So if you are looking for that 35% damage slice the probability is 50% of 1/21= 1/242 = 0.4%
With other words 1 out of 242 slices is a 35% damage slice.
I am not 100% sure about the math, I might be wrong. Please comment. I am a bit surprised that the probability for 35% is that low.
cpz
Sat Mar 05, 2005 1:23 am
#9
Bermag wrote:
On my way home form work today I started to think about the probabilities for various slices. I remembered a post in this forum that showed it to be randomly distributed but however weighted with a higher frequency of mid range slices. I started to think about probability theory and if there is a higher frequency on some slicing% then it could not be one random roll becuase in that case there should be just as many 35% slices as there are 25% slices.
So I come to the conclusion that it must be two random rolls added together. This create a bell shaped distribution of slice results. Just as you throw two dices the most common result is 7, becuase there are more combination of 7 on a six side dice than other choices.
At least with weapons I think it is like this:
Slicing result is 15% + random roll 0-10 + random roll 0-10
Might be other combinations but I could not get the numbers correct (and starting at 0 is common in programming).
This means that there are 11x11=121 possible combinations. If you want to see the possible outcomes then make a grid with numbers 0-10 and you will see the possible combination. The result of frequncies is a triangle form "curve".
To get a 35% (or 15%) there is only one possible combination so the probability to get a 35% slice is 1/121 = 0.8%
The most probable outcome is 25% which is 11/121= 9%
To get 30% or better the probability is 21/121.
However, it get worse :-). There is also a roll if it is speed slice or damage slice which is 50% probability. So if you are looking for that 35% damage slice the probability is 50% of 1/21= 1/242 = 0.4%
With other words 1 out of 242 slices is a 35% damage slice.
I am not 100% sure about the math, I might be wrong. Please comment. I am a bit surprised that the probability for 35% is that low.
Good work. You sort of lost me at "probabilities" but I appreciate the efforts ofmy Smuggler boffin comrades
DigiDante
Sat Mar 05, 2005 1:27 am
#10
It honestly sounds like you nailed it on the head there.
Good post!
If we can get comfirmation on this from a dev, it'd be great to have for a FAQ on how slicing works.
Good post!
If we can get comfirmation on this from a dev, it'd be great to have for a FAQ on how slicing works.
Thehuffermsu
Sat Mar 05, 2005 1:31 am
#11
Fernas wrote:
just so long as we all agree that its random....
hehe well it is but it isn't its randomly distributed but not true random
maxtheusher
Sat Mar 05, 2005 1:35 am
#12
d00dz but sl1c1ng 1sn'T r4ndumb, j00 jUst h4v 2 34t t\/\/1zzl3rz wh1l3 s1ng1ng b4b33 g0t b4ck!!!11!!!!oneone!!
Bermag
Sat Mar 05, 2005 10:30 am
#13
SpinningCloud wrote:Normally an RNG routine call takes a range and returns a value within that range with a distribution at the center of the range. If you ask for an integer between 15 and 35 then it will return a pseudo random number in that range.RNGs come in varieties for C++ that will generate floating point and integer numbers with uniform or nonuniform distributions. The nonuniform distributions can be of normal, bernoulli, poisson, binomial, hypergeometric, noncentral hypergeometric, multinomial, ultivariate hypergeometric, noncentral hypergeometric and shuffling.Why would they code something special when a simple standard function call with the variety offered by C++ RNG functions would suffice?Message Edited by SpinningCloud on 03-04-2005 01:54 PM
You might be right about that. However that much depends on the development tool/framework. Not all have built in "advanced" random function and only have a simple random generator. But you might very well be correct that they may use a random generator with built in normal distribution.
If they don't have bulit in non-uniformal random functions then the easiest way to achieve that is to use two or more "dice rolls" which will give a non-uniform distribution of random results. Not any rocket scinece you make 2 calls to random function.
Anyway the reason I have been thinking of what kind of distribution is used is to know which probability certain slices will have. Not a smuggler myself but weaponsmith and it is good for explaining why a 35% damage slice weapon is so rare and is worth a lot more.
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