# Reinforcement Learning Cube Solver



## abunickabhi (Nov 8, 2018)




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## xyzzy (Nov 13, 2018)

I've found the DeepCube paper to be deeply unsatisfying, but for reasons mostly different from what you mentioned in the video.

The paper claims that they've managed to produce a solver (that is, DeepCube) that rivals the standard Kociemba two-phase algorithm in move count, but this definitely isn't the case. For one, DeepCube is optimised for QTM (which is the metric they use throughout) and they're comparing to an implementation of Kociemba's algorithm that optimises for FTM, so _of course_ DeepCube has an automatic advantage here. I think it's still impressive that they managed to get 30q solutions, but only in the sense that this was achieved with reinforcement learning and nobody else has done it before. It's absolutely not impressive _as a solver_ compared to Cube Explorer.

edit: Oh yeah, I remembered there was a thread for this and I posted there too.


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## abunickabhi (Nov 16, 2018)

I completely agree with you, but we have to keep in mind that these people have no idea about Cube Explorer or standard cube solving algorithms and how they have been used and tweaked over the years.

In the abstract itself, they mentioned that it is a hard problem to do it via reinforcement learning.


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