It is not so surprising since each was visited is only a few times (4-6). But if you look closely you can see that, for example, 19 is found in the target and also over-represented for the last position, and also 39 for the third. In fact, nearly all of these results are relatives of the target. For 6 out of 10, if we add a round of sliding to the top score (as described here), we can recover the target.

If we increase the number of cycles to 5 x 10

^{6}, our target is the clear winner. With this problem, we have 45

^{10}= 3.4 x 10

^{16}positions, so with 4 x 10

^{6}samples, we've clearly improved enormously on random sampling, or more accurately, solved a problem that is nearly impossible by random sampling.

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