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Comment by ionforce | Hacker News Reader

I would love to know why the third match turned sour. I suspect (as an amateur with no ML background) that that matchup was under-trained.

Like I could imagine OpenAI getting stuck in a subset of the draft pool for which it trained against, like maybe the top 10 of 18 champs. And then picking outside of that meta causes it to fall back on much less robust training/strategy.

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Because the first two matches were so lopsided, the bot lineup was selected by twitch chat + audience members. We drafted them a pretty terrible lineup, and from the start the bots estimated their chance of winning to be about 2.9%.

Indeed. And to explain further: not all hero combinations are equal. Meaning: you cannot select any arbitrary set of 5 heroes and expect them to perform well. Different heroes have different strengths and synergies that make them stronger or weaker depending on the specific teammates and opponents that are present. This is why drafting is considered such an important (and difficult) portion of the game. In match 3, a purposefully-bad team was selected. It would have been VERY impressive if it was able to win.

> Meaning: you cannot select any arbitrary set of 5 heroes and expect them to perform well.

When I think of AI, I think of something crawling its way out of purposefully adversarial situations such as this one. I would have loved to see optimal play from 5 wacky heroes.

I just have this suspicion that that wasn't optimal for that team comp.

But of course the matchup itself is a thing.

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