Yes, I agree that your Turing machine approach can model the same
situations, but the different formalisms seem to lend themselves to
different kinds of analysis more naturally...

I guess it all depends on what kinds of theorems you want to formulate...

ben

On Tue, Sep 2, 2008 at 3:00 PM, William Pearson <[EMAIL PROTECTED]>wrote:

> 2008/9/2 Ben Goertzel <[EMAIL PROTECTED]>:
> >
> > Hmmm..
> >
> > Rather, I would prefer to model a self-modifying AGI system as something
> > like
> >
> > F(t+1) =  (F(t))( F(t), E(t) )
> >
> > where E(t) is the environment at time t and F(t) is the system at time t
>
> Are you assuming the system knows the environment totally? Or did you
> mean the input the system gets from the environment? Would you have to
> assume the environment was deterministic as well in order to construct
> a hyperset? Unless you can construct a hyperset tree kind of thing,
> with branches for each possible environmental state?
>
> > This is a hyperset equation, but it seems to nicely and directly capture
> the
> > fact that the system is actually acting on and modifying itself...
> >
>
> I'll use _ to indicate subscript for now.
>
> I think s_n+1 = g_s_n(x) encompasses the same idea of
> self-modification, as the function that g performs on x is determined
> by the state if you consider g to be a UTM and s to be a program it
> becomes a bit clearer. Consider g() and f() to be the hardware or
> physics of the system.
>
>  Will
>
>
> -------------------------------------------
> agi
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-- 
Ben Goertzel, PhD
CEO, Novamente LLC and Biomind LLC
Director of Research, SIAI
[EMAIL PROTECTED]

"Nothing will ever be attempted if all possible objections must be first
overcome " - Dr Samuel Johnson



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agi
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