[ndh2]

Because Starcraft is 1v1 and LoL is 5v5. Poker AIs also focus on 1v1 as opposed to full ring games. It's easier.

Also because Starcraft has three races, i. e. 9 matchups. But if you pick one race for your AI, you only have three matchups to worry about. LoL on the other hand has about 500 champions (give or take), whose strengths and weaknesses are vastly dependent on the current patch. LoL is less about skill or strategy, and more about picking the champion of the week.

Starcraft works because they have such a small number of matchups that balancing them is possible. Certainly not easy, and players keep figuring out ways to evolve the meta game. Maybe an AI could even find interesting new strategies. But LoL has so many matchups that their balancing team has an absolutely impossible task of trying to catch up. It's so complex that they can't just think about in theory, but they have to look at win-rate statistics, over different skill ranges. At this point it's more a problem of data science. And the number of champions keeps growing, because that's how they make money.

[justfor1comment]

  > Because Starcraft is 1v1 and LoL is 5v5
  Starcraft can also be played 5v5
  > Also because Starcraft has three races, i. e. 9 matchups
  But each race has 20 different units. The units are more 
  similar to LOL champions than the races. There are also a 
  tonne of different buildings and upgrades to choose from.
  LOL is very similar to DOTA and given that OpenAI already 
  beat *human* players in DOTA, LOL is not that farfetched. The 
  current work, although impressive, still cannot beat *human* 
  players in SC2. The complexity of designing AI for a game 
  depends heavily on the branching factor of decision in the 
  game. SC2 has a much higher branching factor than LOL or any 
  other games played by n00bs.

[LitFan]

> LoL on the other hand has about 500 champions (give or take)

LoL has 141 champions. Still significantly higher than Dota's 116.

A common note I hear when people discuss open AI playing dota is that it uses pre-made matchups, which reduces the number of matchups considerably.

Would it be that difficult to have the AI play the picking stage? Compared to the complexity of the decisions you have to make during the game, the picks are straightforward - especially if you have performance data on matchups.

The number of practice games the AI would have to play to learn to handle all the heroes goes up drastically, but that's only a matter of time.

[Ajedi32]

They had drafting working just fine in a previous version of the AI. (The one that played against semi-pros a month or so before TI.)

One theory I heard was that the pre-made matchups at TI were designed to prevent the human players from getting out-drafted. (The hero pool was pretty limited, which could result in a different meta from what the human players were used to.) They wanted to make the matches purely a test of in-game skill, not about the metagame. As far as I know though, the OpenAI team hasn't explicitly confirmed that.

[maaark]

I'm pretty sure OpenAI only plays the single simplest hero, mechanically. The other 115 would be varying degrees of "more difficult" to play competently.

Also, it only played mirror matches. If it had to play any hero against any hero, that's 3.393109e+190 possible matchups.

[bilkoo]

I don't think you need to learn all possible matchups to play any matchup, as a human would. You'd need to just learn how to play/counter each hero, plus some 2 or 3 hero combos (not all permutations), so on the order of a hundreds?

[wrsh07]

They've had some updates since then: https://blog.openai.com/openai-five-benchmark/

(Plus two shorter / more recent status updates)