Yeah, true...

On Mon, 21 May 2018, 13:41 Nil Geisweiller, <[email protected]> wrote:

> On 05/21/2018 01:48 PM, Ben Goertzel wrote:
> > But Nil -- those record-keeping links can be put in an auxiliary
> > Atomspace, not necessarily the same Atomspace where the main thrust of
> > reasoning is proceeding...
>
> Yes, but for rules like incremental direct calculation, and TV revision
> in general, it seems traces do need to be taken into account as
> reasoning is taking place. That doesn't mean they have to pollute the
> main atomspace, but it does show that some form of attention allocation
> / meta-learning will be necessary. Well, that is true regardless of that
> problem, it just adds more weight to the scale.
>
> Nil
>
> >
> > On Mon, May 21, 2018 at 8:45 AM, 'Nil Geisweiller' via opencog
> > <[email protected]> wrote:
> >> On 05/19/2018 09:00 PM, Alexey Potapov wrote:
> >>>
> >>> Our knowledge is built from data. Deduction systems (probabilistic or
> not)
> >>> lack this connection, while functional PPLs are well-suited for this.
> >>
> >>
> >> Deduction system can be understood very broadly, and may encompass
> >> inferences based on PPL models as well.
> >>
> >> PLN definitely draws, at least in principle, the relationship between
> >> deduction and data.
> >>
> >> ATM in practice it's a bit lacking though, for instance the link
> between the
> >> TV
> >>
> >> Implication <TV>
> >>    P
> >>    Q
> >>
> >> obtained from instances of P and Q is forgotten after the inference.
> This
> >> should be corrected. Meaning the inference rule
> >>
> >> D ;; <- instances of P and Q
> >> |-
> >> Implication <TV>
> >>    P
> >>    Q
> >>
> >> should be more something like
> >>
> >> LinkBetweenDataAndImplication <TV>
> >>    D ;; <- instances of P and Q
> >>    Implication
> >>      P
> >>      Q
> >> d ;; <- new instance pair of P and Q
> >> |-
> >> LinkBetweenDataAndImplication <TV_update>
> >>    Cons
> >>      d
> >>      D
> >>    Implication
> >>      P
> >>      Q
> >>
> >> It would also provide an incremental way to calculate the TV as opposed
> to
> >> batch processing every time.
> >>
> >> It's kinda scary, computationally wise, but it seems to do well most
> >> inference traces need to be recorded, not just conclusions. Yet another
> >> meta-learning black hole...
> >>
> >> Nil
> >>
> >> --
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> >
> >
>

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