On 21/08/09 2:57 PM, "Frank Berger" <[email protected]> wrote:
> Removing doubles would probably have an influence, but for any > practial purpose even a linear congruent > RNG is good enough so an NN wont learn any pattern > Agreed, removing double would likely have an influence. I made the suggestion as an example of how machine learning may see the game differently based on a bad PRNG. But I whole heartedly agree that its extremely unlikely that the bot would pick up on such a tine and insignificant various as to be seen as anything other than noise. > AFAIK MT is not strong enough for cryptography but these cryptography > algo are very challenging. For any practical purpose it is good enough. Mersenne Twister in itself passes most tests of randomness (Hardened tests etc). But from a cryptographic perspective it is bad because of reproducibility. It can be attacked mathematically in such a way that one could reproduce the seed and then the data given enough data and time. As well, how the seed was originally generated is often targeted if you know the method by which It was generated you can attempt to reconstruct it. > > All this implies that there is an exploitable pattern in the RNG. I > would bet that an NN trained to predict MT would fail We don't disagree on this either. But I wouldn't put bets on the old c/c++ implementations of random() in the old days. They were highly periodic and very untrustworthy as a good source of random numbers. Could an NN trained to predict that fail? I'd say most likely it would fail too (Although it would have a better chance than soemthing like MT) _______________________________________________ Bug-gnubg mailing list [email protected] http://lists.gnu.org/mailman/listinfo/bug-gnubg
