----- Original Message -----
From: "Matt Mahoney" <[EMAIL PROTECTED]>
To: <agi@v2.listbox.com>
Sent: Thursday, May 10, 2007 6:04 PM
Subject: Re: [agi] Determinism
> Perhaps I did not state clearly. I assume you are familiar with the
concept
> of a universal Turing machine. Suppose a machine M produces for each
input x
> the output M(x) (or {} if it runs forever). We say a machine U simulates
M if
> for all x, U(m,x) = M(x), where m is a description of M. One may
construct
> universal Turing machines, such that this is true for all M and all x.
You
> can think of U as predicting what M will output for x, without actually
> running M. In this sense, U can predict its own computations, e.g.
U(u,x) =
> U(x) for all x, where u is a description of U. In other words, U can
simulate
> itself.
I could care less about Turing machines or infinite memories. If you want
to create an AGI, you will have to use real life computers and real life
software, not imaginary musings.
> Turing machines have infinite memory. Real computers have finite memory.
> There is no such thing as a universal finite state machine. If a machine
M
> has n states (or log2(n) bits of memory), it is not possible to construct
a
> machine U with less than n states such that U(m,x) = M(x) for all x. For
some
> x, yes. I assume that is what you mean. This has nothing to do with
speed,
> and makes no distinction between memory in RAM or on disk.
>
> > My example used the output from the formula of a line which produces
> > infinite results from only a Y intercept and a slope. You didn't bother
to
> > show how my analogy was incorrect.
>
> I didn't understand how it was relevant.
A simulation can be as simple as the formula for a line. The formula is the
algorithm that defines the simulation and the input uses this formula to
produce results. This seems pretty simple to me. With the correct
algorithm that has minimal memory or storage requirements, you get an
infinite set of answers. This is certainly a class of models. The human
brain is defined by a small set of instructions encoded by DNA and this
produces the hugely complex brain.
Small input, huge output. The memory requirement for a simulation is not
proportional to the volume of output.
> > I can predict with high accuracy what I will think on almost any topic.
> > People that can't, either don't know much about the principles they use
to
> > think or aren't very rational.
>
> You can't predict when you will next think of something, because then you
are
> thinking of it right now. Maybe you can predict some of your future
thoughts,
> but not all of them. Your brain has finite memory. The best you can do
is
> use a probabilistic approximation of your own thought processes.
I never said I could PREDICT what I would think at some time in the future,
only what I would conclude if I thought about some particular problem. If
you told me I said XYZ 5 years ago, I could tell you with absolute accuracy
if in fact I did say XYZ or not. The reason is that I am meticulously
consistent in the conclusions I draw based on the information I have. This
knowledge of what I know and how I think is not probabilistic or
approximate. It is totally deterministic and intentional regardless of the
inherent non-determinism of my human brain.
David Clark
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