AIs vs Humans - Next Battle: Starcraft (businessinsider.com)

braindrainbahrain writes: Having conquered checkers, chess, and more recently Go, artificial intelligence research now looks at the next frontier: the popular real-time strategy game of StarCraft.
Blizzard Entertainment's president reached out to Google's DeepMind researchers last month, who are now describing StarCraft as "our likely next target". But many top StarCraft experts believe AIs will fail because "Unlike machines, humans are good at lying," reports the Wall Street Journal. An executive at the Korea e-Sports Association tells them "It's going to be hard for AI to bluff or to trick a human player."

One University of Alberta computer scientist David Churchill counters that âoeWhen the AI finds that the only way to win is to show strength, it will do that. If you want to call that bluffing, then the AI is capable of bluffing, but there's no machismo behind it." Unfortuantely, for five years Churchill has been running AI-vs-human StarCraft tournaments, and "So far, it hasn't even been close... Using a mouse and keyboard, the world's top players can issue 500 or more commands a minute," the Journal reports. But they add that now both Facebook and Microsoft are also working on small StarCraft AI projects.

Comments

Data vs the Zackdorn

[spire3661]

Data couldnt beat Kolrami, so he forced him into what would have been an indefinite stalemate. Kolrami found this incredibly insulting and forfeit. Data won by having no ego. He busted him up.....

As An AI Researcher

[Anonymous Coward]

I'm a CS Masters student doing a thesis on a RTS AI. Computers can beat humans, we just haven't tossed enough CPU at it yet. RTS are exactly the same as checkers, chess, go, etc... except you have more pieces, more board positions, and more than one piece can be moved per turn. To reduce that into something computable, you need good abstractions. Once you have those the game becomes a tree search, same as all the board games. Google/IBM can bring enough computing resources to the table to win. There are some bumps in that: imperfect information, teams, etc... but they don't change the core algorithms.

Computing the entire game tree is too expensive. They'll probably do it at a unit/battle level, at a squad level, at a city level, and at a long term strategy level. Doing things at different levels greatly reduces the search space. From your training data you'll know how well you can expect the battle manager to handle an upcoming attack with an expected loss of XYZ at some probability, so the strategy component doesn't need to bother with all the minor details of how to fight it.

500 commands a minute? That's nothing. With the computing resources of a super computer, expect the AI to be able to issue an order to every individual unit every game turn. And yes, at the game engine level all real-time strategy games are actually turn based.

When you have the resources, a tree search over a game's state space with a little bit of memory (so the enemy can't get your units stuck in a circle) is effectively unbeatable.

Re: Computers are no good at lying is that a joke?

[Solandri]

Oh, I know a neural net can learn and tweak its responses based on past experiences. The beauty of bluffing is it can totally screw up that learning process

For years, Ty Cobb famously overran 3rd base instead of stopping every time a certain player fielded the ball. That forced the player to throw the ball to third base to force Cobb back. Eventually the player got used to Cobb overrunning third base and his throws to force him back got lazy and slow. Then one day in an important game with the score tied, Ty Cobb overran third base, the player made a lazy throw to third to force him back, and Cobb broke for home and scored the winning run.

Really good players develop an innate sense for when an opponent is bluffing. I can't explain how it works, but I know it does. When I was kid, I had this innate sense for The Price is Right. I could predict with about 95% accuracy when the announcer was going to say the prize was a new car. I have no idea how I did it, but my subconscious was getting some sort of signal from the inflection of his voice or the delay in his speech or something that told my conscious mind that he was going to say a new car. Ty Cobb was also exceptional at this sort of thing. When a teammate once asked him how he was able to hit so well against a certain pitcher who gave everyone else problems, Cobb replied that the pitcher's ears wiggled every time he was about to throw a curve.

This works when your mind is flexible enough to consider all possible inputs, even the seemingly irrelevant ones. It doesn't work with an AI programmed to look at only a limited number of "important" inputs to keep the CPU load down.