Nil,
> > 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... This might be ok when we are talking about small-dimensional tasks, but I don't think this is a good idea for real-world problems... BTW, one my colleague (Vitaly Khudobahshov) has had some ideas regarding that meta-computations should/can be carried out on low-dimensional instances of problems, and then derived specialized solvers to apply to higher-dimensional instances... So, maybe, it's ok to have LinkBetweenDataAndImplication ... -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/opencog. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/CABpRrhz8fGEjswHTkp3ZuhTKYQLsHSKFj2JCicOORq%2BNXwBSYQ%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
