Google
DeepMind
unveiled
SIMA,
an
AI
agent
training
to
learn
gaming
skills
so
it
plays
more
like
a
human
instead
of
an
overpowered
AI
that
does
its
own
thing.
SIMA,
which
stands
for
Scalable,
Instructable,
Multiworld
Agent,
is
currently
only
in
research.
SIMA
will
eventually
learn
how
to
play
any
video
game,
even
games
with
no
linear
path
to
end
the
game
and
open-world
games.
Though
it’s
not
intended
to
replace
existing
game
AI,
think
of
it
more
as
another
player
that
meshes
well
with
your
party.
It
mixes
natural
language
instruction
with
understanding
3D
worlds
and
image
recognition.
“SIMA
isn’t
trained
to
win
a
game;
it’s
trained
to
run
it
and
do
what
it’s
told,”
said
Google
DeepMind
researcher
and
SIMA
co-lead
Tim
Harley
during
a
briefing
with
reporters.
Google
worked
with
eight
game
developers,
including
Hello
Games,
Embracer,
Tuxedo
Labs,
Coffee
Stain,
and
others,
to
train
and
test
SIMA.
Researchers
plugged
SIMA
into
games
like
No
Man’s
Sky,
Teardown,
Valheim,
and
Goat
Simulator
3
to
teach
the
AI
agent
the
basics
of
playing
the
games.
In
a
blog
post,
Google
said
that
SIMA
doesn’t
need
a
custom
API
to
play
the
games
or
access
source
codes.
Harley
said
the
team
chose
games
that
were
more
focused
on
open
play
than
narrative
to
help
SIMA
learn
general
gaming
skills.
If
you’ve
played
or
watched
a
playthrough
of
Goat
Simulator,
you
know
that
doing
random,
spontaneous
things
is
the
point
of
the
game,
and
Harley
said
it
was
this
kind
of
spontaneity
they
hoped
SIMA
would
learn.
To
do
this,
the
team
first
built
a
new
environment
in
the
Unity
engine
where
the
agents
needed
to
create
sculptures
to
test
their
understanding
of
object
manipulation.
Then,
Google
recorded
pairs
of
human
players
—
one
controlling
the
game
and
the
other
giving
instructions
on
what
to
do
next
—
to
capture
language
instructions.
Afterward,
players
played
independently
to
show
what
led
to
their
actions
in
the
game.
All
of
this
was
fed
to
the
SIMA
agents
to
learn
to
predict
what
would
happen
next
on
the
screen.
SIMA
currently
has
about
600
basic
skills,
such
as
turning
left,
climbing
a
ladder,
and
opening
the
menu
to
use
a
map.
Eventually,
Harley
said,
SIMA
could
be
instructed
to
do
more
complex
functions
within
a
game.
Tasks
like
“find
resources
and
build
a
camp”
are
still
difficult
because
AI
agents
can’t
perform
actions
for
humans.
SIMA
isn’t
meant
to
be
an
AI-powered
NPC
like
the
ones
from
Nvidia
and
Convai,
but
another
player
in
a
game
that
impacts
the
result.
SIMA
project
co-lead
Frederic
Besse
said
it’s
too
early
to
tell
what
kind
of
uses
AI
agents
like
it
could
bring
to
gaming
outside
of
the
research
sphere.
Like
AI
NPCs,
however,
SIMA
may
eventually
learn
to
talk,
but
it’s
far
from
that.
SIMA
is
still
learning
how
to
play
games
and
adapt
to
ones
it
hasn’t
played
before.
Google
said
that
with
more
advanced
AI
models,
SIMA
may
eventually
be
able
to
do
more
complex
tasks
and
be
the
perfect
AI
party
member
to
lead
you
to
victory.
(Originally posted by Emilia David)
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