Shane,

The following is what I wrote in the memo, which basically agrees with
what you said.

"In principle, these three frameworks [dynamical system, inferential
system, and computational system] are equivalent in their expressive
power, in the sense that a virtual machine defined in one framework
can be implemented by another virtual machine defined in another
framework. ... ... Even so, for a given problem, it may be easier to
find solutions in one framework than in the other frameworks.
Therefore, the frameworks are not equivalent in practical
applications."

Pei

On 12/18/05, Shane Legg <[EMAIL PROTECTED]> wrote:
> Pei,
>
>
> > > What you seem to be criticising in your memo is what I'd call
> > > "feed forward neural networks".
> >
> > I see what you mean, though in the memo I didn't rule out feedback.
>
> Recurrence makes all the difference...
>
> For example, consider a very simple neural network model:
> Rational activations, fixed topologies, no learning rules or weight
> changes allowed, and just a trivial linear activation function.
>
> If you allow only feed forward connections then such a network
> can only compute linear functions of inputs.  Pretty dumb.
>
> On the other hand,  if you allow these networks to have recurrent
> connections, the model is in fact Turing complete.  Indeed people
> have built networks in this model that simulate classical universal
> Turing machines (see the work of Siegelman).  There are even
> compilers for high level languages like Occam that will output
> a recurrent neural network to execute your program (see the work
> of Neto for example).
>
> Anyway my point is, once you allow recurrent connections even
> trivial types of neural networks can, in theory, compute anything.
> This is why I prefer to think of NNs as a computational paradigm
> rather than a class of techniques, algorithms or methods.
>
> You could argue that NARS is a better way of thinking about or
> expressing AGI, or something like that, perhaps.  Just as you
> might argue that C is a better way of programming than machine
> code.  However the limitations aren't fundamental, indeed I could
> write a NARS system in Occam and then compile it to run as
> a neural network.
>
> Shane
>
>
>
>
>
>
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