[SeckinJohn]

you'd be better off if you mapped those 10 numbers to a number in [0:(10!-1)] interval since there are only 10! different potential answers. So you make the job of the algorithm easier (figuring out the "structure" of the function it's trying to solve for is easier when the result space is compressed without any 'signal' loss)

another improvement could be "enhancing" of the inputs: when you figure out how you will permute the numbers to sort them, create specific and randomized variations of that specific list of numbers and feed the learning algorithm with the correct results of those permutations too. for instance if you have 5 70 2 13 as a training input, the trainer algorithm could generate the following extra inputs based on this so that the algorithm will get a better chance of figuring out the sorting for a test input like 2 15 5 65:

2 5 23 70 2 5 33 70 ... 2 5 63 70 2 5 73 70 also: 2 5 14 70 2 5 13 69 etc. also modify more than 1 number at the same time(both systematically and also randomly) to generate even more "gray"-input