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DeepMind's AI agents conquer human pros at Starcraft II
AI agents developed by Google's DeepMind subsidiary have beaten human pros at Starcraft II — a first in the world of artificial intelligence. In a series of matches streamed on YouTube and Twitch, AI players beat the humans 10 games in a row. In the final match, pro player Grzegorz "MaNa" Komincz was able to snatch a single victory for humanity.
[...] Beating humans at video games might seem like a sideshow in AI development, but it's a significant research challenge. Games like Starcraft II are harder for computers to play than board games like chess or Go. In video games, AI agents can't watch the movement of every piece to calculate their next move, and they have to react in real time.
These factors didn't seem like much of an impediment to DeepMind's AI system, dubbed AlphaStar. First, it beat pro player Dario "TLO" Wünsch, before moving to take on MaNa. The games were originally played in December last year at DeepMind's London HQ, but a final match against MaNa was streamed live today, providing humans with their single victory.
Professional Starcraft commentators described AlphaStar's play as "phenomenal" and "superhuman." In Starcraft II, players start on different sides of the same map before building up a base, training an army, and invading the enemy's territory. AlphaStar was particularly good at what's called "micro," short for micromanagement, referring to the ability to control troops quickly and decisively on the battlefield.
[...] Experts have already begun to dissect the games and argue over whether AlphaStar had any unfair advantages. The AI agent was hobbled in some ways. For example, it was restricted from performing more clicks per minute than a human. But unlike human players, it was able to view the whole map at once, rather than navigating it manually.
Previously: Google DeepMind to Take on Starcraft II
Google's AI Declares Galactic War on Starcraft
Related: DeepMind's AI Agents Exceed Human-Level Gameplay in Quake III
Move Over AlphaGo: AlphaZero Taught Itself to Play Three Different Games
(Score: 2) by takyon on Saturday January 26 2019, @05:05AM
AlphaDeepWhatever's limitations may be coming into focus. This map thing - if we were to restrict it to using a the normal view of the map (at a screen resolution allowed by the game) as well as the mini-map, and force it to scroll or click as if it were using a mouse, then the problem space could become a lot larger. Suddenly it needs to kind of remember what's going on, and it becomes less of an image recognition problem. It has to react to sound alerts or enemies appearing on the mini-map.
I don't think it's impossible to make it do everything like a human short of physically staring at a screen, tapping on a keyboard, and moving a mouse (which could be done with a robot if we want to go there). But it might (un)expectedly make the problem orders of magnitude harder.
Advances in transistors or 3D architecture could make the hardware thousands or millions of times faster, allowing the problems to be brute forced like before. Or we could see Google move towards neuromorphic and "strong AI", i.e. a machine with apparent sapience. The latter would be developed in secret. And there would be a lot more interesting applications than "Starcraft 2 playing slave".
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