Linas Vepstas wrote:
On Sat, Nov 10, 2007 at 10:19:44AM -0800, Jef Allbright wrote:
as I was driving home I approached a
truck off the side of the road, its driver pulling hard on a bar,
tightening the straps securing the load. Without conscious thought I
moved over in my lane to allow for the possibility that he might slip.
That chain of inference, and its requisite knowledge base, leading to
a "simple" human behavior, are not even on the radar horizon of
current AI technology.
?
"I see a human, better give him wide berth". Certainly, the ability to
detect and deal with pedestrians will be required before these things
become street-legal.
I can easily imagine that next-years grand challenge, or the one
thereafter, will explicitly require ability to deal with cyclists,
motorcyclists, pedestrians, children and dogs. Exactly how they'd test
this, however, I don't know ...
The problem (essentially the "frame" problem) is that it is no good to
say "Oh, we had better code for the situation of avoiding pedestrians,
cyclists, children and dogs", it is that the system needs to be able to
generally model the world in such a way that it can *anticipate*, by
itself, a general situation that looks like developing into a problem.
You never know what new situation might arise that might be a problem,
and you cannot market a driverless car on the understanding that IF it
starts killing people under particular circumstances, THEN someone will
follow that by adding code to deal with that specific circumstance.
The whole question then becomes: just how general are the mechanisms
for understanding that a situation is a "problem" situation (like the
one that Jef posed)?
My understanding of the existing technology is that it is ridiculously
far from being able to represent the world in such a general way that it
could anticipate novel hazards without using up too many pedestrians.
Absent that solution, I don't think these systems are going to be onthe
market any time soon.
Richard Loosemore
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