Stefan
Member
I made this a while ago but didn't quite finish it, now Robert Yau's thread with the hard 2x2x2 scramble reminded me and I decided to publish it anyway:
http://www.stefan-pochmann.info//spocc/speedsolving/RoFL/
edit: "RoFL" means "Rotten First Layer"
If I remember correctly, I also checked *all* RoFL cases (with up to all four pieces rotten), so that would directly include Rob's scramble, and non-rotten was again the worst in HTM and QTM and the best RoFL case for QTM beats non-rotten by exactly one move and the best RoFL case for HTM also beats non-rotten by exactly one move, though the two cases differ. I sadly didn't make nice pages for this analysis, maybe I'll do them later if noone else does. But I'd probably have to redo the whole analysis, even if I find the old files again.
Edit: I just realized that a RoFL automatically means the opposite layer is also a RoFL, so you could always choose between them. And another idea I just had: You could learn algs for a selection of RoFL cases (not just one), where the selection is optimized so that you can always build one of the cases in let's say three moves (so no bad cases like Rob's with its 5 or 6 moves). Or optimize the selection for (weighted) average or so.
Edit: If you prefer, you can also call it RotFL method. I found it hard to decide which I like better.
http://www.stefan-pochmann.info//spocc/speedsolving/RoFL/
edit: "RoFL" means "Rotten First Layer"
If I remember correctly, I also checked *all* RoFL cases (with up to all four pieces rotten), so that would directly include Rob's scramble, and non-rotten was again the worst in HTM and QTM and the best RoFL case for QTM beats non-rotten by exactly one move and the best RoFL case for HTM also beats non-rotten by exactly one move, though the two cases differ. I sadly didn't make nice pages for this analysis, maybe I'll do them later if noone else does. But I'd probably have to redo the whole analysis, even if I find the old files again.
Edit: I just realized that a RoFL automatically means the opposite layer is also a RoFL, so you could always choose between them. And another idea I just had: You could learn algs for a selection of RoFL cases (not just one), where the selection is optimized so that you can always build one of the cases in let's say three moves (so no bad cases like Rob's with its 5 or 6 moves). Or optimize the selection for (weighted) average or so.
Edit: If you prefer, you can also call it RotFL method. I found it hard to decide which I like better.
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