🚀 go-pugleaf

In article <f6xk02b078qO01@amdahl.uts.amdahl.com>
	kp@amdahl.uts.amdahl.com (Ken Presting) writes:
> David Chalmers writes:
>>So while we won't capture the exact behaviour of System X
>>at 3 p.m. on 12/22/89, we'll generate equally plausible behaviour -- in other
>>words, how the system *might* have gone, if a few unimportant random
>>parameters had been different.
>
>These objections seem to grant at least a part of my point - some of the
>characteristics of some causal systems cannot be specified by programs.
>I agree that an AI need not model any particular person at a particular
>time.  But since the error in a numerical model is cumulative over time
>slices, it's not just the behavior of the system at a given time that
>won't match, but also the general shape of the trajectories though the
>state space of the system.

My thoughts:

Let us say you see a leaf falling.  Since you are a chaotic system your
trajectory through space-time may be completely different than it would
be if you did not see that leaf.  But did that leaf make you non
human?  Did it 'kill' you because it changed your future so
drastically?  I don't think so.

Let us say that we model someone on a computer but we do not capture
everything.  Because of the imperfections of the model the resulting
system will diverge.  (Also because the inputs to this system and to
the original are different.)  Isn't that equivalent to the falling leaf
incident? (assuming the model is close enough so it does not cause a
breakdown in the basic things that make a human -- whatever those
are.)  I don't agree that some characteristics cannot be specified by
programs.  They can be specified up to any precision we would like.  I
don't think the human brain is so complex that it has an infinite
number of *important* parameters (that without them you will fail the
'thinking test').  Actually I don't think there are so many $10M will
not capture today (if we knew how to model them).

You also wrote that chaotic systems are specificaly hard to model.  A
computer is a chaotic system.  It is very easy to model a computer.
Therefore it may be possible to model other chaotic systems.  You have
to justify your claim better.

Summary:  Inaccurate modeling may have an effect similar to 'normal'
  events.  Since the inputs will be different anyway, the inaccuracy
  may not matter.

		Miron Cuperman
		miron@cs.sfu.ca