Hi Linas, Thank you for the example:
I think this again helps visualize my further questions: How is this additional conceptual knowledge harvested in a way that mimics human thinking on one hand (i.e. it deploys context adequately, established relevant abstractions, and, generally, creates a structure that is parsimonious, conceptual (i.e. thing, not string), and supports effective and efficient autonomous and goal-directed reasoning over it on the other. And, thinking out loud some more -- what if a lot of common sense knowledge is implicit and not observable. We can observe what people do but its much harder to know why they do it and the connective (socio-psychological-cultural and value-laden (a now favorite word of mine) ) tissue (personal experiences) that holds it all together and gives it explanatory meaning. thank you, Daniel On Friday, 21 April 2017 18:50:33 UTC+3, linas wrote: > > > On Fri, Apr 21, 2017 at 10:12 AM, Daniel Gross <gros...@gmail.com > <javascript:>> wrote: > >> In context of A one morphism may hold, in context B another -- and you >> indicated two kinds of contexts, ) domains (swimming, rowing) and >> human-introspective-valueladen interpretive context. > > > > To return to Alex's original question, there was a question of how to > represent knowledge in a computer. So, for opencog, a very miniscule > subset of the knowledge graph might be: > > ContextLink > ConceptNode "swimming" > EvalutaionLink > PredicateNode "catch" > PhysicalMotorMovementLink > PositionLink... > VelocityLink.... > > that's the general idea. The above is actually a rather poor design for > representing that knowledge: instead of position and velocity, it should be > about hand and wrist. Instead of PredicateNode "catch" it should be > PredicateNode "catch as taught by Mark", with additional links to Mark and > why his technique differs from the catch as taught by coach Ted. So this > simplistic graph representation blows up out of control very rapidly. > Which is why it cannot be hand-authored: its why the system must > automatically discern and learn such structures. > > BTW, in opencog, any two-element link is a "morphism" > > SomeLink > SomeNode "source" > OtherNode "target" > > Its OK to think of that as an arrow from source to target. But its also > OK to think about it as a binary tree, with "SomeLink" being the root, and > the two nodes being the leaves. So there are multiple ways to diagram > these things. > > --linas > -- 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 opencog+unsubscr...@googlegroups.com. To post to this group, send email to opencog@googlegroups.com. 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/d582d660-22b4-41fb-906c-f9423869c8b7%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
