Fill up ESI data...

[KP708]

I've been reading through this thread - fascinating stuff by the way - and there's lots of detailed analysis, but could someone paint an overall picture of what it really means.

I know from my own experience this is not easy to do until you have all the data, complete the analysis and then say - ah this is how it works, and publish your results. However, it all looks so interesting and yet I feel when reading through this that I cannot see the wood for the trees.

For example, there are graphs which show (if I understand correctly) TT value of a skill increment of 1 plotted against skill level. This centres around zero, so some skill increments are negative. This makes no sense to me, as it would imply that at some skill levels the TT would pay you to accept a skill increase of 1 point. Probably I've misunderstood what the graph is plotting, but this sine wave idea seems very weird. Why have a value that oscillates. I know TT value is all code-generated, and not natural phenomena, but is it possible there's another explanation for the perceived sine-wave based variation. Like rounding at an early stage in the calculation inside the servers because the programmer used an integer variable by mistake?

I think I understand the objective here - to be able to predict the TT value of any skill level (is it just an assumption that this is the same for all skills?). But if there is a lot of variation outside of rounding factors, doesn't this mean something else is also affecting the TT values being observed? I mean here that if the formula was say TT = skill delta * X (it's not I know - this is for illstration) then you could find a value for X +/- some error due to rounding issues. But if more than a couple of data points (which could be put down to measurement error) were outside the rounding error range, then the formula is wrong. Because code is perfect. If the skill valuation code in the game has a formula of whatever, this will always give the same answer. If it doesn't, it's not going to be power surges on the server - the code will have been written to bring in the other factors.

So I guess what I'm saying here is could someone summarise the tentative theories which you're hoping to prove/disprove with the data.

I'm keen to see the outcome of this exercise - a fascinating project

[jdegre]

Originally Posted by KP708

So I guess what I'm saying here is could someone summarise the tentative theories which you're hoping to prove/disprove with the data.

I'm keen to see the outcome of this exercise - a fascinating project

Hi KP,
The objective is, as you said, to find the function that maps a number of skill levels to the tt value of a chip holding these skills.

The immediate application of this function would be to develop a calculator to know how much valuable are the skills in your avatar. There is one at the moment in www.entropiatools.com, which is excellent, but unfortunately it is outdated, since the function was changed in VU 8.9 (i think) and it has not been updated with the new one.

Another useful appliaction would be to know how much would it cost to chip in (and which skills) to reach a certain level in a pro standing, so you can unlock a certain skill. And calculate the cheapest way to do it, of course. (I'm working on this right now... may have something ready soon...)

The function is pretty clear up to a certain level 6-7k, but for higher levels is quite unknown yet. Actually we don't have a clue (well, at least I don't), what's the tt value of 15k skill levels, for instance.

Regarding the sine wave and so, no, definitely, there are not negative skill gains It is simply that the function can be approximated for the curve y=x*exp(x) up to a level of 6-7k, quite accurately; but on top of that, you get a sine-like curve super-imposed to the exp curve.

The sine-like curve can be approximated too, to get a super-exact approximation for the range 6-7k, but I think that for practical purposes, it is quite ok to approximate the overall curve via polynomial interpolation, in the same way that was done in the skill calculator I mentioned earlier.

So, this is basically it. The problem now is that to improve the curve approximation for higher levels, we need people with uber skills to check very big chips and see how they skill increase goes for a certain tt value.

Yesterday I found a massive marksmanship chip (>1k ped tt), in Joker's shop. It would be great if someone with MMS level around 8-9k could check the chip and post what's their skill gain.

Cheers,
/jdegre.

[KP708]

Originally Posted by jdegre

It is simply that the function can be approximated for the curve y=x*exp(x) up to a level of 6-7k, quite accurately; but on top of that, you get a sine-like curve super-imposed to the exp curve.

Thanks for the overview - this makes a lot of sense.

So total value of skill level x = x*exp(x)? ignoring the sine component, and ignoring constant factors? Just making sure this is not value of 1 skill increment, and I'm understanding what you a representing with the formula - sorry for being pedantic.

Why is it called an esi, when it has skills in?

[jdegre]

Originally Posted by KP708

Thanks for the overview - this makes a lot of sense.

So total value of skill level x = x*exp(x)? ignoring the sine component, and ignoring constant factors? Just making sure this is not value of 1 skill increment, and I'm understanding what you a representing with the formula - sorry for being pedantic.

Why is it called an esi, when it has skills in?

yes, the function is something like y = x*exp(a*x+b), you can find "a" and "b" in previous posts, ignoring the sine-like component.
"x" is the skill level, and "y" is the tt value of the chip, in peds. (it works more or less in the interval 500 < x < 6000).

skill chips are not called esi's when they have skills in them. they are called "skill implants".

/jdegre.

[Jimmy B]

OK, Bogger kindly gave me his NRF data in exchange for trying to find a rough estimate as to a decent chipping path to Commando for him.

I used the calculator linked earlier in the thread to estimate the costs of ESI (in 500skill batches for each relevant skill) where I could, otherwise I just guessed it. (anything>7500)

If someone has the time to check I've done nothing stupid I'd be grateful, the results can be seen:

http://spreadsheets.google.com/pub?k...AE1gPvuZadP5dA

Keep up the good work, its useful stuff.

[jdegre]

Originally Posted by Jimmy B

OK, Bogger kindly gave me his NRF data in exchange for trying to find a rough estimate as to a decent chipping path to Commando for him.

I used the calculator linked earlier in the thread to estimate the costs of ESI (in 500skill batches for each relevant skill) where I could, otherwise I just guessed it. (anything>7500)

If someone has the time to check I've done nothing stupid I'd be grateful, the results can be seen:

http://spreadsheets.google.com/pub?k...AE1gPvuZadP5dA

Keep up the good work, its useful stuff.

Hi Jimmy,
I've run Bogger's data through my calculator and I've got the following results:

Initial Laser Pistoleer: 5588
Final Laser Pistoleer: 7009
Total Cost: 56002 ped

Aim: 4473
Combat Reflexes: 4214
Combat Sense: 4913
Handgun: 10144
Marksmanship: 6205
Weapons Handling: 6015
Laser Weaponry Technology: 7595
Dexterity: 3648

So, even when the function I've used is different from Doer's, and the resulting final skills are different than yours, the total cost is amazingly similar (and also the subset of skills to chip and not to chip); nice...

My program uses basically the same approach than your spreadsheet, but in an automated way, so I can do more iterations with a smaller increment (you used 500, and I use 50).
Currently the program is developed in Java; I'm working on a web-based version so it can be easily used by other people.

I've noticed the "10% uncertainty" margin you added at the end of your calcs, and yes, unfortunately it can be even higher than that, specially for those high skill levels (~10k) where the function "level->tt" is not fully known yet.

Cheers,
/jdegre.

[Jimmy B]

Thanks Jdegre, yeah doing it by hand with 50 increments wouldn't have been much fun

Nice to see them come out reasonably similar

Your approach has particularly picked out more Handgun, which isn't necessarily all that surprising as I had to go by complete guesswork for the Handgun skill Vs Implant tt

Bogger will be pleased - 750 PED less

[Bogger]

ty Jdegre and Jimmy now i just wait as price of ESI continues to tumble lol

[Doer]

Sorry i've been super busy lately. KP708, what you were probably looking at was one of the plots of the sinusoidal part of the curve. As jdegre mentioned, the level->tt value function has the form y=sin(x)*z+*x*exp(x) from 550 to at least 7.5k. Somewhere above 7.5k the nature of the function changes significantly. Unfortunately, no one fit of the x*exp(x) curve fits the entire range from 550 to 7k, so i have been breaking it into segments and fitting the segments with their own exp() function. The sin function remains the same except for a possible change in factor at a couple places, though.

I do have to disagree with jdegre that a poly fit will be sufficient for getting optimal results (at least not without breaking it into short enough segments to approximate the sine, which we don't have enough data for at high levels). You can see that the error is greatly reduced by including the sin function in the fit:


The average error is much smaller with the sin and exp fit (black line) vs just the exp() function (red line). Sure the sine can be ignored for low skill values, but by the time you get to ~8k skills, the magnitude of the function is about 20 PEDs, which as a percentage may not be much, but in absolute terms is huge. With my fit that includes a sine wave i get less than 1% error over almost the entire range we have data for.

Here's the fit of my current function to the data we have:


I spent some time creating a new spreadsheet to simplify trying different fits and data sets. When we have a good fit to 8k+ i will focus on the chip calculator i have been wanting to do, and been detoured by the need to finish the skill<->tt fit.

This is not the function currently used by the php script i have linked earlier. I will update that script when i'm satisfied with the 900-1.1k range, which is a bit high with the parameters i'm using now.

[jdegre]

Originally Posted by jdegre

My program uses basically the same approach than your spreadsheet, but in an automated way, so I can do more iterations with a smaller increment (you used 500, and I use 50).
Currently the program is developed in Java; I'm working on a web-based version so it can be easily used by other people.

Sorry for quoting myself
Just wanted to share a draft version of the "chipping optimizer" program (web version). Try this link:

http://jdegre.net/pe/unlocker.php

It is quite straightforward to use: just select the profession from the drop down list (only a few available so far), enter some skills, your current level is calculated as you type, and enter the target level, and click "go"; you should get the optimal path to get to your target level, and the total cost. The level is displayed as 1-10k to avoid decimals.

If you have locked skills, leave that field empty and it will not be considered in the calculations.

Let me know what you think.

Cheers,
/jdegre.

PS.: Keep in mind that this is very dependent on the skills->tt function, which is extremely unreliable for levels > 7-8k, so you better don't trust too much on those values.

PS2.: Some interesting finds is how much it costs to unlock MMS (~275 ped), RDA (~1150 ped), Seren (~4200 ped), Coolness (~11k ped), etc... starting from level 1.