Earlier this year, Google’s
AlphaGo AI successfully beat world-class champion Go player Lee Se-dol
in four games out of five. This was a significant milestone,
thanks to the sheer number of positions that are possible within the
game, and the difficulty of creating an AI that could efficiently
evaluate them before the heat death of the universe. Now, Blizzard is
teaming up with Google to create a next-generation AI capable of playing
an actual computer game: Starcraft II.
At first glance, this might not seem to make
much sense. After all, playing against an “AI” has been a feature of
computer games for decades, in everything from first person shooters to
RPGs, to chess simulators. The difference between game AI and the kind
of AI Google is developing is simple: Most of what we call artificial
intelligence in gaming is remarkably bereft
of anything resembling intelligence. In many titles, increasing the
difficulty level simply gives the computer player more resources, faster
build times, inside information about player activities, or loosens
constraints on how many actions the CPU can perform simultaneously. It
turns the bots into overpowered thugs, but doesn’t really make them better at what they do.
Game AI isn’t really what you’d call “intelligent,” and when it breaks, the results can be hilarious
Game AI typically makes extensive use of
scripts to determine how the computer should respond to player
activities (we know Starcraft’s AI does this because it has actually
been studied in a great deal of depth).
At the most basic level, this consists of a build order for units and
buildings, and some rules for how the computer should respond to various
scenarios. In order to seem even somewhat realistic, a game AI has to
be capable of responding differently to an early rush versus an
expansionistic player who builds a second base, versus a player who
turtles up and plays defensively. In an RPG, a shopkeeper might move
around his store unless he notices you stealing something, at which
point a new script will govern his responses to the player.
An example of AI scripting in Age of Kings
Game AI, therefore, is largely an illusion,
built on scripts and carefully programmed conditions. One critical
difference between game AI and the type of AI that DeepMind and Blizzard
want to build is that game AI doesn’t really learn. It may respond to
your carrier rush by building void rays, or counter your siege tanks
with a zergling rush. But the game isn’t actually learning anything at
all; it’s just reacting to conditions. Once you quit the match the
computer doesn’t remember anything about your play, and it won’t make
adjustments to its own behavior based on who it’s facing.
The AI that Google and Blizzard want to build
would be capable of learning, adapting, and even teaching new players
the ropes of the game in ways far beyond anything contemplated by
current titles. It’ll still be important to constrain the AI in ways
that allow for humans to win, since games like Starcraft are (to a
computer) basically just giant math problems, and an unconstrained CPU
opponent can micro at speeds that would make the best Korean players on
Earth weep.
According to Oriol Vinyals, a research
scientist with Google DeepMind, the company is looking forward to the
challenge. “It’s a game I played a long time ago in quite a serious
way,” Vinyals told Technology Review.
“And as a player, I can attest that there are many interesting things
about StarCraft. For instance, an agent will need to learn planning and
utilize memory, which is a hot topic in machine learning.”
It’s still not clear how easily these
initiatives could be translated back into shipping games; Google’s
AlphaGo is based on its own custom tensor processing units (TensorFlow)
and a varying number of CPU and GPU cores ranging from 48 CPUs and one
GPU to 1,920 CPUs and 280 GPUs. Either way, you’re not going to be
setting up a home system to handle your gaming unless you happen to live
in a server room. This doesn’t mean that computer games couldn’t
benefit from these kinds of projects, though. If Blizzard can teach an
AI how to play Starcraft, it may well be able to teach the AI how to
generate scripts and decision trees that accurately model its own play.
The idea of an AI that teaches a game how to
play Starcraft 2 against humans might sound like science fiction, and
neither Google nor Blizzard has proposed anything quite this advanced.
But it wouldn’t surprise me if that’s the big-picture, long-term idea.
After all, what’s the point of teaching a computer to play Starcraft 2
if humans never get to play against it?
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