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One quick little thought, is theoretically, it should be possible to use PCA to come up with the most significant axes of the roborumble, and rank robots by how well they correlate with each axis. Then, you also rank robots by their standard deviation. You then pick robots which simultaneously have a low standard deviation, and highest correlation with the axes that the PCA determined. Then you can use some linear regression to determine the weight to give each of the robots selected.

That I think, would probably be a good way to find a testbed which simultaneously represents the rumble well and has low noise... Hmm... maybe I should make a patch to Voidious' testbed maker that uses the algorithm I describe in the paragraph above...