Timeline for Can neural network discover rng patterns
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
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| Sep 9, 2017 at 12:24 | comment | added | hyde | Of course it is also a matter of definitions. I feel this link is somehow relevant: xkcd.com/221 | |
| Sep 9, 2017 at 12:09 | comment | added | hyde | About "if you know the function that is generating the sequence of numbers, then all you need is the last number pulled and you're done" , if it can't produce same number twice in a row, it's so low quality I would not call it PRNG... Entire internal state is needed, last number pulled isn't ever enough. If there is no internal state, it's not a real PRNG. I'd edit that sentence a bit. | |
| Mar 12, 2015 at 16:25 | comment | added | riwalk | @MSalters, you most certainly can predict the state as long as you know the details of the algorithm and have a large number of outcomes to analyze. PRNG's are never judged or analyzed based on a single outcome. | |
| Mar 11, 2015 at 16:02 | comment | added | MSalters | This answer seems to mix seed, state and outcome of a RNG. In general, the initial state is a function of the seed, state evolves by repeatedly applying a function to it, and the outcome is determined by yet another function to the state. In a good RNG, the state space is a lot larger than the output domain, so one output can be the result of many different states. In turn that means you can't predict the state nor the next outcome from a single outcome. | |
| May 19, 2012 at 9:57 | vote | accept | formatc | ||
| May 19, 2012 at 3:30 | history | edited | Robert Harvey | CC BY-SA 3.0 |
added 76 characters in body
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| May 19, 2012 at 1:55 | history | edited | riwalk | CC BY-SA 3.0 |
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| May 19, 2012 at 1:49 | history | answered | riwalk | CC BY-SA 3.0 |