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Grandmaster level in StarCraft II using multi-agent reinforcement learning

deepmind.com

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Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#171

Post by [deleted] »

jrx wrote: post #159
interblag wrote: post #59

This is a really interesting one to digest. As with previous announcements about AlphaStar, much of the feedback (here and elsewhere) is about the fundamental challenge of assessing human vs. machine in an RTS. These points are very valid - stepping back however, this still feels like a pretty incredible accomplishment. I'm a gold league SC2 player, so maybe in the 30th-50th percentile. Three years ago, when DeepMind…

> This is like if the world's best chess AI had gone from losing high school tournaments to being competitive with Kasparov in less than 3 years. I don't think it's like that at all. On the high level, there is no "chess AI", "go AI", "image classification AI" and "dexterous manipulation AI". These are all sides of the same coin, that gets significantly better every year. Adding support for the new game or new "envir…

[deleted]

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#172

Post by linuxftw »

sinuhe69 wrote: post #125
linuxftw wrote: post #100

Earlier quoted context omitted.

Because that's all they're capable of doing with it. Games can be easily repeated, have clear outcomes. There's no need for nuanced thinking or actual problem-solving. Just approximate the current scenario against previously successful strategies and pursue that strategy. A real challenge would be to invent a new game, have both a human and an "AI" read the rules for the first time, and then compete in their first ga…

There is no deep learning without massive data. What do you expect? :D

I expect less hype and more substance. I don't think computers beating people at video games (or really, any games) is particularly novel at this point, nor do I think it qualifies as "AI".

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#173

Post by SketchySeaBeast »

pps wrote: post #154
300bps wrote: post #136

Earlier quoted context omitted.

Starcraft is an incredibly complex game. Even basic strategies will win if they’re done faster. APM (actions per minute) is a very significant factor into who is winning. Apparently they limited their AI player to 264 APM but that’s still incredibly high and done with machine level consistency. That’s almost 4.5 actions per second!! I know there are human level players at and probably above that level but that really…

264 is not that high. People (if Serral is not a cyborg) can achieve even 1000 APM; and ~300 EPM average for a game.

Those aren't meaningful actions, though, are they? That's 17 actions a second.

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#174

Post by VIPMaster »

UserIsUnused wrote: post #151
Shaanie wrote: post #103

Earlier quoted context omitted.

Is that supposed to be a joke? DotA doesn't rely on reflexes nearly enough for that to matter.

Data doesn't lie. When so many player play a game, even an almost irrelevant advantage can tip the scale. Or maybe it's a sociological factor, not a phisics ones. But the data doesn't lie.

Sure, data doesn't lie, but where is the data? I'm a pretty seasoned DotA player myself and this is the first I'm hearing of any such phenomenon. I can't think of any hero that shorter players have been more successful on than taller players, or vice versa.

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#175

Post by skybrian »

Mirioron wrote: post #144
gwd wrote: post #66

Earlier quoted context omitted.

> These extremely difficult/impossible things didn't really give an advantage. One of the videos I watched compared APM (Actions Per Minute) with EPM (Effective actions Per Minute). AlphaStar always has them nearly identical, which would be (according to him) basically impossible for humans.

Of course it's impossible for humans. Humans are used to clicking multiple times to do an action. Some actions you want to take in the game are very important, failure to do them correctly can mean a lost game, for example moving units in combat properly. This means that it's better to spam click that action a few times to make sure that the button press is registered properly, because it is possible for button press…

Hmm, seems like it might be interesting to add a slight error rate for AI clicking and see how it handles it?

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#176

Post by NoodleIncident »

bsaul wrote: post #58

Has anyone read the actual paper ? This summary really makes it look like "mission accomplished", but this was much much more interesting than that. We saw AI do "obviously stupid things", and we also saw them improve a lot in the middle of the trial, as many youtubers showed. AI was also much more interesting when playing the protoss race, and really felt like it was responding to the opponents actions, and the othe…

This sounds like it was posted before the link was changed, but at least one pro was impressed by its novel style:

> AlphaStar is an intriguing and unorthodox player – one with the reflexes and speed of the best pros but strategies and a style that are entirely its own. The way AlphaStar was trained, with agents competing against each other in a league, has resulted in gameplay that’s unimaginably unusual; it really makes you question how much of StarCraft’s diverse possibilities pro players have really explored.

- Diego "Kelazhur" Schwimer, professional StarCraft II player

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#177

Post by emiliobumachar »

PeterisP wrote: post #107
the_af wrote: post #99

Earlier quoted context omitted.

Do you mean Google should write a better AI than the one in Civilization? Interesting. But also consider this: in casual strategy videogames -- actually, strike "strategy" and just consider videogames -- most players don't want a really hard opponent. A computer opponent that is really very hard to beat is not what we want, because that'd be frustrating and many of us play videogames (yes, even strategy games!) to un…

In strategy games like Civilization the "preferred" difficulty level is that hard/easy to beat because it gets extra resources. It would be preferrable to have the same difficulty level through opponents that play better/smarter while having the same game mechanic consequences as players if they make the same actions, but we currently can't, so they get artificial production multipliers and such.

Current civ A.I.s may not be the smartest that the Civ team could do. Sid Meier once said on video that on play tests, when the A.I. would do something brilliant, players would just assume it's cheating.

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#178

Post by skybrian »

floitsch wrote: post #49
mieseratte wrote: post #30

Earlier quoted context omitted.

> For humans that would be almost impossible, because the screen would scroll when the mouse approaches the border. That humans cannot reliably perform these actions because of the limitations of our corporeal form means that Alphastar has an advantage over a human player. Limiting APM isn't enough.

The question isn't whether the AI still has advantages, but whether it's an unfair one. The current restrictions were implemented with input from TLO, and seem to work quite nicely. One could, of course, add more restrictions (like not noticing things on the minimap all the time...), but that's not what's it about anymore. At this point, micro is comparable to humans, and we can start to compare macro and strategy. F…

I think it's less about fairness and more about what's interesting? When the AI finds an advantage that makes its gameplay kind of boring, nerf it somehow to see what else it can do.

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#179

Post by frei »

300bps wrote: post #136
minblaster wrote: post #81

Earlier quoted context omitted.

Starcraft is an incredibly complex game. 10^26 possible moves at any point (you can click/drag anywhere on the screen, pressing a keyboard button as you do so), imperfect information, real-time constraints, etc.

Starcraft is an incredibly complex game. Even basic strategies will win if they’re done faster. APM (actions per minute) is a very significant factor into who is winning. Apparently they limited their AI player to 264 APM but that’s still incredibly high and done with machine level consistency. That’s almost 4.5 actions per second!! I know there are human level players at and probably above that level but that really…

>264 APM

Actually 792 APM. They limited their AI to 264 "things" (choose unit+ability+target or change view) per minute. Each "thing" can be counted as between 0-3 actions by starcraft. So it really has a peak APM limit of 792.

From the article:

>Agents were capped at a max of 22 agent actions per 5 seconds, where one agent action corresponds to a selection, an ability and a target unit or point, which counts as up to 3 actions towards the in-game APM counter. Moving the camera also counts as an agent action, despite not being counted towards APM.

But from replays it has an average APM of 248 at the highest, so nothing crazy going on. Plenty of pros have peak APMs during fights that are higher than 800.

Re: Grandmaster level in StarCraft II using multi-agent reinforcement learning

#180

Post by alexeldeib »

diminoten wrote: post #135
dang wrote: post #126

Earlier quoted context omitted.

This comment was originally posted on https://news.ycombinator.com/item?id=21408024 , but we've merged it into the earlier submission, which used the link you mentioned.

The viewers of HN need Nature just as much as anybody, stop deluding yourself into thinking this is some kind of ivory tower...

It's about the original source, per the guidelines.
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