AlphaStar: The inside story

In recent years, StarCraft, considered to be one of the most challenging Real-Time Strategy (RTS) games and one of the longest-played esports of all time, has emerged by consensus as a “grand challenge” for AI research.

Our StarCraft II program AlphaStar is the first Artificial Intelligence to defeat a top professional player. In a series of test matches held on 19 December 2018, AlphaStar decisively beat Team Liquid’s Grzegorz "MaNa" Komincz, one of the world’s strongest professional StarCraft players, 5-0, following a successful benchmark match against his team-mate Dario “TLO” Wünsch. The matches took place under professional match conditions on a competitive ladder map and without any game restrictions.

[wdai]

The alpha go documentary was pretty good, this would make a nice sequel

[russellthorburn]

I was gratified to see how gracious the players were in the face of such a defeat.

[TheAIEpiphany]

We need a game called Alpha so that DeepMind can create AlphaAlpha in a truly alphaic way.

[dr_flunks]

Congrats DeepMind. You're an impressive team.

[userNo]

I'm not yet completely satisfied in Alphastar.

1) The APM cap has to be changed. Alphastar had lower mean APM than the human pros but in engagements its APM shot up to 1500's. That equals 25 actions in a second. No human player is capable of doing this with great precision. The APM should be capped in two ways. Firstly, the mean averge per minute as they did in this demonstration but more importantly, Alphastar should be restricted in such a way that the huge spikes are not possible. Perhaps a limit on how many actions it is allowed to do within a second?

2) Especially in the games against Mana, Alphastar demonstrated inhumane ability to control its units. It won game 4 because of how clean its micro was, not because it outplayed Mana. Good army control is impressive and clearly requires a certain level of intelligence but this kind of perfect blink stalker micro doesn't really exist within the game. Deepmind should differentiate between the agents intent and execution. Perfect micro is more than just speed. Precision is much more important. Human pros missclick all the time. There needs to be a random element in how Alphastar controls its units.

3) The agents seemed to be stuck on the strategies that they had trained in. I'm not entirely sure if this is the case but I think there was zero tech switches from Alphastar. It seemed to be stuck on the army compositions it initially chose. In a few games the composition was clearly sub-optimal considering what the human player had. Reacting to the scouted information and actually being able to flexibly adjust strategy on-the-fly is exactly the kind of intelligence that Deepmind should strive towards.

While Alphastar is impressive and Deepmind limited its mechanical ability a little it was still very clear to someone familiar with Starcraft that it won mostly because of its superhuman mechanical ability. It could perceive all of its own units at the same time, it had superhuman mouse precision and macro abilities.

TL;DR Cool but not quite there yet. Alphastar won because of superhuman mechanical abilities. I want to see a bot that plays as slow and as sloppy as the average pro player and still be able to achieve >50% winrate against the best in the World.

[marianpazdzioch]

I like how Alphastar worked around APM limitation basically by saving up his available APMs for when they are needed most and then use them in bursts :)

[AG-djbc]

For the sake of us, i only hope that your ia safety team is the strongest of all.

[ManjulaBandara]

Came here after the AlphaGo Full Documentary. Impressive stuff!

[polesetter_]

Please make this a full docu as well. Alphago was one of the best docus of the past years.

[elimurphy-trotzky]

Being able to se the whole map at once is an incredibly massive advantage.

[rodrigoserafim]

I am glad our AI overlords are learning so quickly to defeat our puny human armies. I also hope they learn to read youtube comments so they know how much us loyal subjects love them.
bº*r#i+n$g h)e]l&p
sorry for that, must have pressed my elbow against the keyboard.

[bigchunk]

This work inspires me to get into computer science.

[kwanarchive]

The thing about AI that people underestimate is that the volume of automated training can quickly help an AI to overcome the mistakes in its learning.

With humans, it's very hard to convince someone they're wrong, let alone change someone's mind, and often you just have to breed new humans and hope the old ones die off fast enough so that their mistakes don't get meaningfully passed on to the next generation.

[ClipCourt]

Major Fan of AlphaStar overcoming programming complexities for a better future.

[tomchrysostomou]

Brilliant, brilliant, brilliant, Deep Mind has done it again! Well done, very impressive!

[tripleaaaa]

I know it had superhuman micro, but let's talk about how amazing it is that it plays human strategies so well, and plays like a human.

[akamezo]

Now it is the time to see the clash of A.I : OpenAI Five VS DeepMind AlphaStar .

[VramsGamingChannel]

It's amazing how calm these pros are when they lose. I get flustered and upset and if I lost 5-0 I'd feel humiliated. They let it slide off like water to a duck's back.

[Loppy]

Vote up if you want to watch AlphaStar vs Serral

[jonathanwalther]

Model human decision making. Model an army. Model a map. Use enough time and computing power. The military is already knocking.