Stardew Valley has two random number seeds. One is the normal character seed. The other, your multiplayer ID, can be determined by analyzing the save file.
Except! On the Switch, you can't easily access the save file AND the random number generator is different than on PC. There is a seed cracker that looks at your traveling cart listing and calculates the character seed. Maybe because it's less important and harder to observe, I haven't found any tool to crack the other seed and don't have time to attempt writing it myself.
By inspecting cracked geode contents, you should be able to isolate your multiplayer ID and then predict random events on Nintendo just as PC players have done for the last decade with access to the save file.
The C# code for the game is online and the Switch RNG is known, so you never have to work in the dark. It's three steps: ensure your Switch RNG implementation works by testing against the normal seed, ensure your geode RNG implementation works by testing against the PC RNG, and then apply the Switch RNG to the geode function enough times that only one seed could create your observed sequence.
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Two semi-related open questions: Are you able to solve as quickly while starting at ANY geode as you'd be solving from the first geode? Does the RNG eventually repeat, so it actually doesn't matter what your multiplayer ID is as long as you observe a unique sequence, since there will only be one continuation of that sequence?
My favorite is the Doom random number generator, which is just a list of “random” numbers that it cycles through and if you know how to use it, you can do things like concentrate BFG attacks.
Reminds me of a "Dice" electronics kit I assembled when I was a kid. It just used some standard sequential counter ICs run at very high rate. Pressing the "roll" button would just stop the counter!
> We chose taus88 mainly because it is the fastest from boost’s generators.
That's an RNG from 1996. It seems neither recent C++ standards, nor boost, know anything about the modern PRNGs that are much faster yet better at passing test suites
One of the reasons I dislike boost is in the first code sample. What’s the point of implementing what boils down to a 10 line function (as shown in the decompiled output) like this
TL;DR: Wired up an in-game predictor of RNG output and used it to only craft legendary items when RNG would line up to roll legendary.
From base to legendary at a suprisingly high rate. Look very closely at the video at the top of the post - what I was seeing didn't sink in until I had finished the article. Amazing.
I did an easier version of this in my college intro class. There was a class competition that involved rock paper scissors as a subcomponent, and ties were broken with randomness. You could rig Java’s prng so you would win all ties.
The prng was seeded with usec time at first call. I called the rng a bunch of times to harvest entropy, and scanned the plausible usec times to find the seed. Then I primed the prng so I would win ties.
Frankly, I assume I implemented this wrong, but the theory was there lol.
I am failing to find the article, but some early online poker systems used the server time as the seed coupled with a weak PRNG. With the information of the hole cards + community cards, after a few hands, could quickly determine exactly what seed was being used and perfectly predict everyone's cards.
That’s not at all what the article proposed. The author constructed and transpose to the linear shift register coefficients and built a circuit network based on this to predict the next state (in the sandbox) and direct recipes.
> Calculating corresponding quality levels for each future call, and finally
> Making use of the predicted levels with some adapters.
The entropy->seeds (internal RNG state) step took more math of course. Frankly, I wouldn’t be surprised if they could have extracted the seeds without the math with a bit of RE and memory inspection.
The version I did wasn’t predicting quality of course, it was predicting tie breakers
by far the blackest magic I ever saw for that game.
I'm an upper intermediate at Factorio, resorting to someone else's blueprints only for belt balancers and rail intersections, and I can't even begin to figure out how it's done.
Stardew Valley has two random number seeds. One is the normal character seed. The other, your multiplayer ID, can be determined by analyzing the save file.
Except! On the Switch, you can't easily access the save file AND the random number generator is different than on PC. There is a seed cracker that looks at your traveling cart listing and calculates the character seed. Maybe because it's less important and harder to observe, I haven't found any tool to crack the other seed and don't have time to attempt writing it myself.
By inspecting cracked geode contents, you should be able to isolate your multiplayer ID and then predict random events on Nintendo just as PC players have done for the last decade with access to the save file.
The C# code for the game is online and the Switch RNG is known, so you never have to work in the dark. It's three steps: ensure your Switch RNG implementation works by testing against the normal seed, ensure your geode RNG implementation works by testing against the PC RNG, and then apply the Switch RNG to the geode function enough times that only one seed could create your observed sequence.
-----
Two semi-related open questions: Are you able to solve as quickly while starting at ANY geode as you'd be solving from the first geode? Does the RNG eventually repeat, so it actually doesn't matter what your multiplayer ID is as long as you observe a unique sequence, since there will only be one continuation of that sequence?
My favorite is the Doom random number generator, which is just a list of “random” numbers that it cycles through and if you know how to use it, you can do things like concentrate BFG attacks.
:)
the closely related not-at-all-random fizzlefade from Wolfenstein: https://fabiensanglard.net/fizzlefade/
Reminds me of a "Dice" electronics kit I assembled when I was a kid. It just used some standard sequential counter ICs run at very high rate. Pressing the "roll" button would just stop the counter!
EverQuest also used pre-generated numbers. The randomness was derived from the large number of players using the same list.
That sounds like a pretty strong source of true randomness, frankly.
(It's then filtered through the list, so the list needs to have good pseudorandomness properties anyway, but still.)
As if Factorio wasn't addictive enough, now we can predict ore patches! My sleep schedule is already ruined.
Factorio players reverse-engineering an RNG? Peak Factorio. The dedication to optimize everything, even randomness, is truly something.
What’s the goal here with posting AI comments on every post? Does it help you get a job, do you sell this account?
> We chose taus88 mainly because it is the fastest from boost’s generators.
That's an RNG from 1996. It seems neither recent C++ standards, nor boost, know anything about the modern PRNGs that are much faster yet better at passing test suites
EDIT: Ok the above quote was from 2014, and boost seems to know some now! https://www.boost.org/doc/libs/latest/doc/html/boost_random/...
One of the reasons I dislike boost is in the first code sample. What’s the point of implementing what boils down to a 10 line function (as shown in the decompiled output) like this
Boost predates C++11
Super cool
Yeah, no notes. It's remarkable.
TL;DR: Wired up an in-game predictor of RNG output and used it to only craft legendary items when RNG would line up to roll legendary.
From base to legendary at a suprisingly high rate. Look very closely at the video at the top of the post - what I was seeing didn't sink in until I had finished the article. Amazing.
Dedication like this is awesome. Finally, we can optimize those starting resource patches without endless map restarts!
If you're playing/hosting locally you get a preview of the world and can reroll for a different seed if you'd like.
At the conclusion, he said he spent two years on this! That's a thesis.
I did an easier version of this in my college intro class. There was a class competition that involved rock paper scissors as a subcomponent, and ties were broken with randomness. You could rig Java’s prng so you would win all ties.
The prng was seeded with usec time at first call. I called the rng a bunch of times to harvest entropy, and scanned the plausible usec times to find the seed. Then I primed the prng so I would win ties.
Frankly, I assume I implemented this wrong, but the theory was there lol.
I am failing to find the article, but some early online poker systems used the server time as the seed coupled with a weak PRNG. With the information of the hole cards + community cards, after a few hands, could quickly determine exactly what seed was being used and perfectly predict everyone's cards.
That’s not at all what the article proposed. The author constructed and transpose to the linear shift register coefficients and built a circuit network based on this to predict the next state (in the sandbox) and direct recipes.
From the article:
> Sampling the current RNG through observations,
> Computing the current internal RNG state,
> Predicting the future internal states,
> Calculating corresponding quality levels for each future call, and finally
> Making use of the predicted levels with some adapters.
The entropy->seeds (internal RNG state) step took more math of course. Frankly, I wouldn’t be surprised if they could have extracted the seeds without the math with a bit of RE and memory inspection.
The version I did wasn’t predicting quality of course, it was predicting tie breakers
Really cool example of how something that looks random can become predictable once you understand the underlying system.
neat! more info on LFSRs, fyi: https://www.embeddedrelated.com/showarticle/1309.php
by far the blackest magic I ever saw for that game.
I'm an upper intermediate at Factorio, resorting to someone else's blueprints only for belt balancers and rail intersections, and I can't even begin to figure out how it's done.
Impressive work!
Madman. Brilliant.