#santa-2023
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i think not many people have started working on the competition yet, that's why
Why not?
its quite new
plus I think many people won't try this challenge till the playground series competition is donr
im trying to use reinforcement learning for this one
but it is very slow and annoying
but from my initial tests
i have brute forced the 2x2x2 cubes and an RL agent solved them in less time
so i hope this generalises...
You'll have to train an agent for each puzzle type no?
my testing is nowhere near complete but i think there are 4 possibilities
1 - 1 agent for each puzzle
2 - one agent for each puzzle type
3 - intuition (ignore impossible actions)
4 - domain specific action space reduction (https://arxiv.org/pdf/2004.00980.pdf)
how many time for solve using brute force?
Well it depends on the particular puzzle
For now im working on the 2x2x2 cubes
And it will generalise
for the 30 instance of 2x2x2
Actually I'm solving the 30 2x2x2 in 7 seconds. I don't think ML can be faster than that
I got the RL agent to do it in 10 miliseconds per move
But RL can't prove the quality of the solution, or can?
no
not easily
but my thought process was that for the 100x100x100 cubes it would be very hard
Dom, how long are your episodes?
as brute force scales (N^1โ1)!
depends on the problem
for 2x2x2 i have found 80 to be good
Well how much memory did the 2x2x2 take? In GB?
brute force or DQN?
Brute force
Did you throw in actual good paths in your replay buffer from the brute forced graph?
well there are 3674160 states
and from each state i found the fastest path to a solution
so quite a bit at peak
like 6gb
Not too bad. I just feel like it won't generalize well if you parametrize the action space to try to handle larger cubes
well yes
but there is some evidence that it could work
thats what experimentation is for
Indeed. It'll be interesting how it works with the 3x3 ones
yeaj
yeah*
also I have worked with RL agents and a changing action space in the past briefly
I think that brute force not works on 3x3x3.
I will try localsearch to improva a poor solution
yeah
but when you get to 100x100x100, even local search will be impossible hard to do
no?
You have too many actions you could do lol
The best idea I think will be to just build out the graphs starting from the solution state
And then sprinkle in known good paths with the random garbage patjs your agent starting from random init state
33x33x33 is the max, no?
how do you represnt the state? If that's not a secrete
yeah mb
i was thinking wreath_100/100
what do you mean?
e.g. Do you just use one-hot for each position?
I was thinking of somehow representing the puzzel using a graph, and then do GNN. But couldn't think of a good idea
I made sure that my representation was rotationally invariant so it is actually slightly less large
Nice
I am working on a different representation that removes colour symmetries
and reflectional ones too
but i havent used such maths in a long long time
Have GNNs ever worked for anything
damn solved ~all 2/2 and 3/3 cubes ~optimally and got 24th place
I thought it would be top 10
cause I miscalculated the score
which is the best puzzle type to focus on next?
Holy number 1 got sub 200k
At this point I am sure that people started to use ML models, or supercomputers ๐
well I'd expect everyone is using ML models
but yeah this is a very compute heavy contest, I'd expect the top spots have a decent number of large gpus
I think this server is now my own personal journal
solving the 4/4s is haard
my ubuntu keeps killing my program because it's taking too much memory
or maybe it's killing it for some other reason, my GPU's memory is only 50% full ๐ค
yeah dmesg says it's out of memory
weird
I'm still bruteforcing 2x2x2 
I wrote something on Efficient Cube deep learning algorithm on Discussions and published one code on Codes.
It could be a starting point for a DL approach if you are not using it already.
Sorry for the code being too messy
I don't see it?
Is it possible that the solution of the cubes is more than the theoretical maximum because the cube must be "aligned" in the correct direction? Or that shouldn't play any role? I am just bothered by the fact that a solution of my brute force approach on 2x2x2 has 2 of the same moves one after the other (e.g. '-f0', '-f0') and I'm tryin to explain that.
wait, I think I got something wrong. Initially I thought both 90 and 180 degrees movements were allowed, but apparently they are not. That probably means that the maximum number of moves should be higher than I first expected. And having 2 of the same move is totally fine
the name of the discussion and the code is "Efficient Cube"
Max is 26
But also I think you're right about the orientation
But I didn't see any cubes over the maximum
I also posted about efficientcube with TPU a while ago https://www.kaggle.com/discussions/general/405935
Rubik's Cube solving using kyo-takano's efficientcube with TPU.
Sorry, I thought you were talking about the 333
so on the 2x2x2 max is 14?
hey! I made an interactive 3D viz with plotly of any NxN rubik's cube:
https://www.kaggle.com/code/edomingo/rubik-s-cube-3d-interactive-viz-plotly
let me know if this could be useful ๐
Hi! i made a sollution that i want to submit but it needs 24hours (estimation)
i didn't make any optimisation and all calculations are on cpu whith no multi threading
Is there a processing time limitation on the challenge ? (first time i really try kaggle challenges and didn't find the information for this one)
You only need submit .csv file. There is no limitation.
It can take as long as you like on your own hardware and you can simply submit the resulting csv file, but if you choose to run it in Kaggle, they have a 12-hour limit on CPU jobs.
yes, 14 (according to google/chatgpt)
Ughhh reinforcement learning is so annoying... Time for evolutionary networks i guess
Did you grab a stablebaselines model? Or did you write your own?
actually an interesting problem to tackle
given the sparse reward structure
i wonder if anyone will come up with something worth publishing
I'm thinking that move history does matter right? So we can penalize an agent for reversing a move, or doing the same one 4 times. Does that sound about right?
Possibly, maybe not moves but revisiting states. But thats seems implicit in the -1 per step formulation
Yes but, would be useful to find if the fact that the orientation of the solution needs to be specific, causes any increase in the total number of moves.
Otherwise I get that the max moves are indeed 14 in a normal scenario
Hi everyone! I am looking for a teammate for this competition. I am currently rank ~30 (changes a lot) and I would love to discuss possible approaches to the problems.
@forest cipher Happy to send a team request for your consideration, currently looking to fill up our team slots with complementary ML and algorithm skillsets.
the leaderboard is crazy. 74321???????
now is 72407 ๐
In about 2 days 19 hours from now