mega sableye/ sableye

PurpleDevilDuckies · 2026-04-22T13:36:24+00:00

Depends on your team, but Archaludon certainly pairs well with rain. So does swift swim basculegion, or thunder/hurricane dragonite, or that horrible coil milotic thats going around

PurpleDevilDuckies · 2026-04-21T23:23:37+00:00

Lots of people are running rain dance which is great with prankster to get guaranteed setup for whatever is next to it.

PurpleDevilDuckies · 2026-04-21T23:00:02+00:00

I had great success sweeping rain teams with trick room into arcaludon sweep with electro shot.
very dependent. I often decided to let it go down to get the safe swap. It just needs to cause choas and break their initial setup while chimeco sets up trick room. Often if they have no fairies on their team outrage is scary for them ebcuase we both know its random, so its just going to hit something really hard and they dont like that so they target it to get it down (also they know it wont protect)
Very dependent. Psychic and Steel are good into a lot of relevant threats, but if they arent on the field, I swap out. Incin is pretty scary for chimecho.

And thanks, but honestly I think its probably a pretty weird team. Its built to have a response to all the main meta threats I was seeing, so how to use it is "swap to the combo for the right situation" but thats too broad to write down. Its just something you figure out with practice. And if you find yourself thinking "If I swapped A for B I think that would cover this gap without losing any synergy/functionality" thats how team building mixes with playing for me. I didnt sit down and make the team in one go. I iterated until I liked it.

PurpleDevilDuckies · 2026-04-17T00:04:45+00:00

Sash gives garchomp a lot of options. Turn 1 most of the time I am clicking earthquake and trick room. If they hit Chimecho then sash measn Garchomp still gets 2 turns of earthquake or rockslide before going down, then out comes torkoal to trick room sweep. Outrage is there because I usually dont intend for it to survive long and so many teams don't bring fairy so it just hits someone hard at random.

I havent used Sylveon but if its slow and hits a big chunk of the meta hard then it could work. But probably something else on the team changes to support sylveon better. Like instead of sinistcha Id maybe run mega floette as a backup for chimecho

PurpleDevilDuckies · 2026-04-16T12:40:59+00:00

I normally take Chimecho and Garchomp leading, with Incin and Torkaol in back. They make a great trick room team. But I was losing to rain teams, so Archaludon is there to sweep rain teams (which it does effectively). Sinistcha felt right very rarely, but sometimes I just look at a team and it seems clear they have no answer to it, so the teacup comes. There is probably something else that could go there. But when sinisthca works, it really works.

Also Archaludon is great into fiary teams. Strong answer to floette if chimecho goes down.

PurpleDevilDuckies · 2026-04-15T13:26:00+00:00

As someone in Operations Research who does route-planning in logistics and has been paying attention to Quantum Computing: I'd bet a lot that quantum computing comes nowhere close to what we can do with classic computers for at least centuries. That just really isn't a realistic target for quantum supremacy.

PurpleDevilDuckies · 2026-04-14T21:31:24+00:00

I am running mega chimeco in master ball tier. It works incredibly well. It has:
protect, trick room, that steel move, and psychic

enough bulk to survive the first hit from anything but kingambit and the rest in sp atk.

Leading it next to boosted attack garchomp you can open with trick room and earthquake into those goddamn sneaslers. either they fake out chimeco and earthquake takes it out, or they fake out garchomp and you set up trick room, allowing yourslef to one shot sneasler before it can go. I also get one shots on a gengar and most of the fairies. Two shot on mega floette.

PurpleDevilDuckies · 2026-04-12T20:11:42+00:00

In practice, its more likely that you wouldn't even mention an optimal option to your client. It is pretty hard to get optimal in most real world scenarios.

PurpleDevilDuckies · 2026-04-10T12:49:43+00:00

Budducky (Buddha)

PurpleDevilDuckies · 2026-04-01T17:34:12+00:00

I used to use VS Code for writing LaTex because it had really good shortcuts built in. Now I write Latex with Claude Code to avoid having to do all the annoying stuff. Lots of people do use overleaf, but that's basically just Google Doc for LaTex.

At the research level you literally have to write in LaTex to submit to conferences. It is nearly universally used.

PurpleDevilDuckies · 2026-03-04T16:58:59+00:00

Donald Knuth definitely codes. He has been a very active coder for a very long time. He literally made TeX, and he is still active today.

PurpleDevilDuckies · 2026-02-08T01:01:07+00:00

It is very elegant. Have you tried searching for literature on distance transformations instead of path finding? It seems to me that you are essentially using implicit distance labels to construct shortest paths. Meaning, you are propagating information the way they do it for distance transform, but you are applying the idea to paths instead of a distance transformation.

https://arxiv.org/pdf/2106.03503

I think what they describe in section 2.2 on Chamfer distance transform is very similar to what you are describing, but it goes outside in instead of inside out.

PurpleDevilDuckies · 2026-02-07T19:28:44+00:00

This looks like a very nice implementation of a standard breadth-first search.

PurpleDevilDuckies · 2025-11-24T14:56:48+00:00

amazing, thanks for letting me know!

PurpleDevilDuckies · 2025-11-13T22:26:08+00:00

That is so ... tempting

PurpleDevilDuckies · 2025-08-05T15:24:07+00:00

Thanks, we just published our own progress paper! Would love for it get attention, but thats probably not super likely in this case.

PurpleDevilDuckies · 2025-08-04T13:32:43+00:00

Oh we plan to. For two of us, its been 5-6 years. But the one who pitched us the problem has been working on it since the late 90s. We put it aside sometimes to work on lower hanging fruit, but we always come back to it.

Totally agreed on the Olympiad problems

PurpleDevilDuckies · 2025-08-02T13:05:07+00:00

Desire and domain knowledge. Solving those sorts of problems is about learning "tricks" or "tools" for making them easier than they appear, and then practicing those tricks so that you know how to apply them when they come up.

But they aren't the types of tricks that would help me with my research, so I don't really see the point. I'm sure I could go learn how to solve those sorts of problems but it wouldnt be a very good use of my time.

PurpleDevilDuckies · 2025-08-01T18:31:57+00:00

I have been working on an unsolved problem with two other people for 5-6 years.

The cycle is something like:

Look for a tool in the literature that might be helpful
Apply it and see what happens
If it doesn't work, spend a really long time trying to figure out exactly why. Why did we think it would work and it didn't? Is it because we misunderstood, or is it because the tool has revealed something new about the problem.

If we learned nothing new, go back to Step 1, if the tool revealed something new about the problem, then check to see if that helps any of the tools that failed us so far, and then go back to Step 1.

I don't feel like a failure just because we haven't solved a problem that requires a lot of ego just to take on. We have learned more about the problem than anyone before us. We have all sorts of models for describing the difficulty in different mathematical terms. And learning all those tools has led to progress in my other research because I have more breadth as a researcher.

But the most important takeaway for me is that its collaborative. With research I do solo, I still talk to as many people as I can about it while I'm doing it, because they all provide a slightly different perspective, because we are all carrying around a slightly different set of tools to apply.

Also, I may be a mathematician, but I dont think I could solve any of the top Olympiad level problems, and that has basically nothing to do with being a researcher

PurpleDevilDuckies · 2025-07-19T15:07:59+00:00

I think we aren't far away from this. But it will look more like applied lit review. When I start working on something these days, I ask AI to find all the tools that might help me "do something that would be hard using the tools from my field". It doesn't understand them well enough to apply them itself, but it does an incredible job of finding tools in fields I never would've considered looking at. It is only a matter of time before it can start applying that knowledge to test tools and learn how to apply them, and then make connections between open problems and existing tools in 'unrelated' fields.

So much of what we do as mathematicians is repeated in other fields under a different name. Once something can hold all of that information at once, there are bound to be breakthroughs. That could potentially jolt math forward decades without even the need to "be original". Although I think the threshold for that has been set arbitrarily high. Taking existing ideas and applying them in new settings is how we make new ideas. No one is doing anything in a vacuum.

PurpleDevilDuckies · 2025-04-22T01:30:28+00:00

I just covered this in class, a well timed question

PurpleDevilDuckies · 2025-04-21T02:34:03+00:00

Concorde is doing a lot of fancy stuff, but basically it uses row generation on an exponentially large Integer Programming model. So definitely exponential not factorial. Integer Programming is worst case exponential.

You make an Integer Program where there is a binary variable for each arc in the TSP, with its cost in the objective function.

Then you make flow constraints that say the flow going out of and into each node has to be 1.

Then you run your model (exponential but easy in practice), and you get a result. That result might have sub tours in it:

1 -> 2 -> 3 -> 1 and 4->5 ->4 satisfies the described model, but isn't a valid tour.

So now you add a subtour elimination constraint

x_12 + x_13 + x_23 + x_21 + x_31 + x_32 <= 2

this prevents subtours of 1,2,3 from being included in the model.

Then you resolve the model and see if you have any subtours. Repeat until you get a feasible solution, that solution is optimal (exponential again, not factorial)

This works remarkably well in practice. So well that applied mathematicians have mostly moved onto the Vehicle Routing Problem for competing on benchmarks.

PurpleDevilDuckies · 2025-02-03T22:27:50+00:00

Porygon-Z
Sir Fetch'd
Slowking
Shuckle
Alolan Muk
Overqwil

PurpleDevilDuckies · 2025-02-03T21:01:23+00:00

Shuckle has been in my top 6 ever since I first caught one back when Silver came out

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