>> I agree about developmental language learning combined with automated >> learning of grammar rules being the right approach to NLP.
I think that the fundamentals of grammar rules are hard-coded into humans and that the specific non-determined details (i.e. language-specific differences) are (relatively :-) quickly picked up by specifically evolved parts of the brain (i.e. not a generalized learning mechanism). Why are you insisting that using a generalized learning mechanism to learn grammar rules is an effective approach? It looks to me like *learning* grammar could be skipped entirely. ----- Original Message ----- From: Benjamin Goertzel To: agi@v2.listbox.com Sent: Saturday, April 28, 2007 9:02 AM Subject: Re: [agi] rule-based NL system I agree about developmental language learning combined with automated learning of grammar rules being the right approach to NLP. In fact, my first wife did her PhD work on this topic in 1994, at Waikato University in Hamilton New Zealand. She got frustrated and quite before finishing her degree, but her program (which I helped with) inferred some nifty grammatical rules from a bunch of really simple children's books, and then used them as a seed for learning more complex grammatical rules from slightly more complex children's books. This work was never published (like at least 80% of my work, because writing things up for publication is boring and sometimes takes more time than doing the work...). However, a notable thing we found during that research was that nearly all children's books, and children's spoken language (e.g. from the CHILDES corpus of childrens spoken language), make copious and constant reference to PICTURES (in the book case) or objects in the physical surround (in the spoken language case). In other words: I became convinced that in the developmental approach, if you want to take the human child language learning metaphor at all seriously, you need to go beyond pure language learning and take an experientially grounded approach. Of course, this doesn't rule out the potential viability of pursuing developmental approaches that **don't** take the human child language learning metaphor at all seriously ;-) But it seems pretty clear that, in the human case, experiential grounding plays a rather huge role in helping small children learn the rules of language... -- Ben G On 4/28/07, J. Storrs Hall, PhD. <[EMAIL PROTECTED]> wrote: I think YKY is right on this one. There was a Dave Barry column about going to the movies with kids in which a 40-foot image of a handgun appears on the screen, at which point every mother in the theater turns to her kid and says, "Oh look, he's got a GUN!" Communication in natural language is extremely compressed. It's a code that expresses the *difference* between the speaker's and the hearer's states of knowledge, not a full readout of the meaning. (this is why misunderstanding is so common, as witness the "intelligence" discussion here) Even a theoretical Solomonoff/Hutter AI would flounder if given a completely compressed bit-stream: it would be completely random, incompressible and unpredictable like Chaitin's Omega number. Language is a lot closer to this than is the sensory input stream of a kid. There's a quote widely attributed to a "William Martin" (anybody know who he is?): "You can't learn anything unless you almost know it already." In general, the hearer needs a world model almost the same as the speaker's. Let's call this "Winograd's Theory of Understanding": that having a model capable of simulating the domain of discourse is necessary and sufficient for understanding discourse about it. (NB: (a) there are different levels of completeness and accuracy for simulations and also for understanding; (b) "symbol grounding" in the sense of associations to physical sensory/motor signals is *not necessary*.) I find SHRDLU and its intellectual descencents a convincing demonstration of WTU. This implies that understanding an NL sentence consists not only in parsing it into an internal representation and stashing it somewhere, but, if it's something you didn't already know, modifying and augmenting the mechanism of your world model to reflect the new knowledge in future simulations. In other words, building a working mechanism and integrating it into an existing vast, complex machine. Josh On Saturday 28 April 2007 03:29, YKY (Yan King Yin) wrote: > "Layered learning" is not just better, it's actually the only > computationally feasible approach. > > We may talk to a baby like: > "MILK?" > "You want to play BALL?" > "Oh you POO-POO again" etc. > And these things are said simultaneously as some *physical* events (eg > milk, ball, poo) are happening, which allows the baby to correctly *bind* > the words to concepts, ie achieve grounding. > > Contrast this with something from Wall Street Journal: > Headline: "Employees of a new plan to get Dell back on the road to growth, > including streamlining management and looking at new methods of > distribution beyond the computer company's direct-selling model." > Can a baby really learn from THIS ^^^ ? ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?& ------------------------------------------------------------------------------ This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?& ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=fabd7936