Alexey, *** Our knowledge is built from data. Deduction systems (probabilistic or not) lack this connection, while functional PPLs are well-suited for this. ***
I don't understand why you think this way... The semantics of probabilistic logic systems can be naturally framed in a fully observation-based way, which is what the original PLN book is about... It's true that a logic system, as part of its formulation, makes some commitments about the initial logic rules, which are not initially derived from the data but rather supplied by the system designer OTOH a probabilistic programming system, as part of its formulation, makes some commitments about the initial programming language primitives, which are not initially derived from the data but rather supplied by the system designer And then there are well known mathematical mappings btw assumptions about logic rules, and assumptions about programming language primitives So why do you think the latter are more suited for being built from data? >From my view it's intuitively sort of the opposite -- I have very detailed picture of how the semantics of PLN is built up from a system's observations, whereas I don't have such a detailed picture of how a functional PPL's semantics is built up from observations. OTOH from a math rather than intuitive perspective I can see it's all the same shit... -- Ben On Sat, May 19, 2018 at 8:02 PM, Alexey Potapov <[email protected]> wrote: >> The difference between a theorem proving >> based AI and a program learning based AI is merely an “implementation >> detail” ;-) … > > > Well, true, but the devil is in the implementation detail. -- Ben Goertzel, PhD http://goertzel.org "Only those who will risk going too far can possibly find out how far they can go." - T.S. Eliot -- 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/CACYTDBf9_TKnpE%3DTPgCo3nWC5N_riZmWk%2Bh1G5%3DT7KLbRkrciQ%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
