On 6/12/07, Mark Waser <[EMAIL PROTECTED]> wrote:
>> a question is whether a software program could tractably learn language without such associations, by relying solely on statistical associations within texts. Isn't there an alternative (or middle ground) of starting the software program with a seed of initial structure and then letting it grow from there (rather than relying only on statistical associations -- which I believe will be intractable for quite some time).
It is at least conceivable. The idea is that you give the system reasonable means to build models (= simulations). The "initial structure" lets the system build approximate models to at least some minimal but not isolated amount of texts. The system then should have some explorative means to build new more complicated models (the hard part). The model extension should be guided by parts of (partially or approxiamtely) interpretable texts that "do not quite fit" (e.g. have uninterpreted words). The extensions are then evaluated by their "predictive" characteristics (how much new text can be consistently interpreted in them). Also, have a look at Polyscheme, etc. ----- 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=e9e40a7e
