My initial amiibo experiments, and some general updates

Finals are coming to a close, and I now have some time to experiment with amiibo. I’ve already linked you to other literature on Ultimate amiibo, but now we’re going to create some of our own.

I have trained two Mario amiibo since launch. The first, named Wall Luigi, is an amiibo that was trained in Smash 4 and carried over. Wall Luigi was never a very good amiibo – of the five Marios that I trained, he was my worst one by far. I transferred him in to Ultimate and trained him, using the expected setup: tournament legal stages while playing as his character, and using the moves I want him to use. That nugget of Smash 4 amiibo training is still functioning in Ultimate.

I taught him to use his up smash and forward air, but eventually introduced the up air as well: it’s a useful, fast attack that keeps the opponent in the air. It was pretty similar to Smash 4 training in most regards, except I wouldn’t normally teach them to use aerials. I’ll be honest, I half-assed his training. Most of his training happened while I was on my lunch break at work, or after a very long and tiring shift. Once he hit level 50, I stopped training him. He really shouldn’t be a very good amiibo.

The second amiibo, named Shapiro (I couldn’t think of anything else) was precisely what the Amiibo Dojo mentioned: turn off the Learn button at level one, and leave it off. At level 50 have them fight. He’s just the base Mario AI dressed up in a wedding outfit. There’s nothing special about him, really.

These are my observations of the Mario amiibo:

  • Effectively uses aerials for the neutral
  • Has difficulty recovering
  • Can gimp with forward air, but not with other aerials
  • Doesn’t appear to favor a smash attack any longer, instead opting to use aerials (could be due to my training method)
  • Favors FLUDD and uses it to gimp
  • Needs to lay off the coffee: Mario jumps around like nobody’s business

 

Wall Luigi and Shapiro have been going at it for a while now, and these are my observations of their battles specifically:

  • On platformed stages, the amiibo that stays a full hop off the main stage is the one that wins
  • On flat stages, the amiibo that stays a short hop off the main stage is the winner: being on the ground gives you a 50/50 shot at being the first one to hit, and being too high means you’ll get hit from below every time
  • Grabs don’t play into the game very much because neither amiibo likes to stay grounded
  • Wall Luigi (the hand-trained one) got his butt handed to him by Shapiro (the AI one)

Let’s talk about that last point for a second. This was a Mario v. Mario match. The stages were all perfectly tournament legal, and their characters were the same. In ditto matches like these, the only difference between the opponents is their training. Of four matches, Wall Luigi only won the first: Shapiro won the next three. Wall Luigi learned after the first match… and then started losing. Shapiro’s AI was so innately strong that he stayed the same but started winning each match. Could turning the Learn button off be the optimal choice for amiibo trainers?

Anyway, the Amiibo Dojo has concluded their first amiibo tournament and they’ve added it to their tournament results here. Ironically enough, their spreadsheet looks a bit like my stat sheet from Smash 4…

Amiibodatasheet5142018.PNG
It’s probably a coincidence

While we’re on the subject of tournaments, the Amiibo Doctor will be doing our own tournament in the near future! I’m not going to be able to do it until after Christmas thanks to a surgery, but I will be offering some sort of prize. I’m currently thinking a small Amazon gift card will do nicely. Everyone will be welcome to submit an amiibo to this tournament, as I don’t believe in excluding anyone when a metagame is this small.

That’s all for today, folks! There’s a lot more research to get done, and hopefully we can soon have more concepts laid out. I’m going to be training some other amiibo next, and we’ll have an observations post laid out for that one as well. Once we have some tournament footage, then I can also adjust the recommended rulesets to make more sense.

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