Re: Where is behavior AI now?


Gordon McComb wrote:
dan michaels wrote:
I'm not quite sure what you meant by this last comment, but an obvious
case where a simple state-machine breaks down and doesn't handle
short-term history [memory] well is the repetitive collision loops that
Tim.P mentioned.

OTOH, have you ever seen a bump-and-go toy get stuck in a corner?

Is the real issue large enough memory to record a history, or limited
programming in ways to render the problem moot in the first place.




It's not really a matter of how "much" memory, rather mainly the
ability to record history and recognize habitual pattern loops. You can
arrange ways to handle simple and specific problems, like getting out
of corners, but for very general purposes of intelligence, you just
cannot rely on randomness to solve your problems.

Also, panicking as a valid mode of "intelligent" behavior is just not
an option, by definition. To postulate a life-n-death situation, you
don't want your sentry robot going into panic mode and killing
everything in sight that moves, etc, or panicking and jumping out of
the top-floor window because the elevator is broke. On and on.



Though not necessarily as efficient in all cases, using a random
solution to getting out of a corner may be just as effective as going
through a known sequence, the latter of which would imply storing a
history of the failed attempts.

Even Tim's solution, which I find elegant in its simplicity, doesn't
need a history to work. Panic is an excellent behavior. In us it might
rise from some chemical excreted each time we try something that doesn't
get us out of a jam. We don't actually need to keep a history of what
we've tried and what we haven't. At some level, we go into panic mode,
becoming in effect a bump-and-go toy. At that level, we're not thinking
rationally, and histories be damned. Funny thing is that this behavior
is endemic to us and most living creatures.

If we're really going to get into behaviorism, we need to look at the
random factor and include irrational thought processes. What I find
lacking in most trials of behavior-based AI and robotics is that the
behavior is too Spock-like. What we might term "negative" behaviors can
be powerful problem solvers, and there are billions of examples of these
negative behaviors in biology.



The Spock problem of BBR is due to the fact the behavioral repertoires
and cognitive abilities of present-day bots are just too limited in the
first place. To use a street term, they're just plain dumb, and can't
do very much. Especially if they have no ability to learn built in in
the 1st place. You can get some variation in behavior "emerging", as
Brooks talks about, but still not like real intelligence.

Randomness or irrationality might play a part, but what you really need
is a huge cognitive and behavioral repertoire to work off of in the
first place. Creativity, I think, comes from having a large #examples
stored in your internal knowledgebase that you can piece together in
different combinations.

.

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