On 09/01/2008, Benjamin Goertzel <[EMAIL PROTECTED]> wrote: > Let's assume one is working within the scope of an AI system that > includes an NLP parser, > a logical knowledge representation system, and needs some intelligent way to > map > the output of the latter into the former. > > Then, in this context, there are three approaches, which may be tried > alone or in combination: > > 1) > Hand-code rules to map the output of the parser into a much less > ambiguous logical format > > 2) > Use statistical learning across a huge corpus of text to somehow infer > these rules > [I did not ever flesh out this approach as it seemed implausible, but > I have to recognize > its theoretical possibility] > > 3) > Use **embodied** learning, so that the system can statistically infer > the rules from the > combination of parse-trees with logical relationships that it observes > to describe > situations it sees > [This is the best approach in principle, but may require years and > years of embodied > interaction for a system to learn.] >
Isn't there a 4th potential one? I would define the 4th as being something like 4) Use a language that can describe itself to bootstrap quickly new phrase usage. These can be seen in humans when processing dictionary/thesaurus like statements or learning a new language. The following paragraphs can be seen as examples of sentances that would need this kind of system to deal with and make use of the information in them: The word, "on," can be used in many different situations. One of these is to imply one thing is above another and supported by it. The prefix dis can mean apart or break apart. Enchant can mean to take control by magical means. What might disenchant mean? * ---End examples It requires the system to be able to process this statement then add the appropriate rules. It may be tentative in keeping or using the rules, gathering information on how useful it finds it while processing text. It is different from handcoding, because it should enable anyone to add rules after a minimal set of language description language has been added. It should be combined with 3 however, so that rules don't always need to be given explicitly. I think this type of learning/instruction has the ability to be a lot quicker than any system that mainly relies on inference. I don't know of systems that are using this sort of thing. And it is a bit above the level I am working at, at the moment. Anyone know of systems that parse and then use sentances in this fashion? Will Pearson * I'm unsure how much work people are doing on the use of prefixes and suffixes to infer the meaning/usage of new words. I certainly use it a lot myself. ----- 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=8660244&id_secret=84031297-d3814e
