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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: 3, Interesting) by RandomFactor on Saturday January 26 2019, @04:46PM
Sure but that generally holds for humans also :-)
If you are in a competition of any sort, then the same constraints should apply to all. However, for real world applications, we certainly want AI to have all those cool advantages.
Put an AI in command of, say, ocean going warships [npr.org] and I want them to be able to pull data from every radar, lidar, microwave, sonar, camera, magnetic, pressure, recon by fire, subspace, and whatever-the-heck-else they have simultaneously and avoid issues like no human ever could (particularly at the dreary end of an extremely long day [soylentnews.org])
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