My idea of Conceptual Typing is not a deductive language (like the Lambda Calculus or something) and it is not an inductive language (like a contemporary programming language). this means that it will have certain possible valuations that were undefined. However, it could be used like a deductive or inductive language. Another problem is that some values may represent poor definitions since it is intended to be a part of an AGI program that can learn through trial and error..
So, I would say that this idea of conceptual typing that I have is impossible to work with. However, because I am willing to consider simpler versions there are so many possible variations that it will prove to be very interesting at the least. The words in a commentary cannot be treated as mere tokens, they must be conceptually interrelated. However, since words have many meanings a program has to figure out the right meaning in order to figure out all the details of the conceptual typing works. I am thinking that based on some experience, the problems of using conceptual typing may be simplified to the point where the method could be used as a way to help determine the meaning of a commentary quicker than can be done using methods that are commonly used today. Of course, I won't know if this idea works until I can try it. Jim Bromer On Thu, Aug 15, 2013 at 10:43 AM, Jim Bromer <[email protected]> wrote: > I believe that concepts play different kinds of roles when they > interact with other concepts. These roles can have functional > implications. So from there I would say that concepts have types. > There are types in programming of course but because concepts are more > dynamic, the typing tends to be more elusive. The recognition that > concepts do have types might make it easier to distinguish what is > happening when concepts are used together. > > Looking at the categories that words belong to can provide some > insight into what I am talking about. The idea that the most general > semantic classes of grammatical analysis might be used to better > understand how sentences are formed has created a number of exciting > theories. But this idea can be taken much further into the narrower > semantic categories that words can take, and I believe that the > evidence is there that it should be. > > For instance, a word like, "captain" might be classified as a proper > noun but it is obvious that the possible associations with the term > are much more extensive than that. I believe that if the semantic > categories that are relevant to a particular sentence become more > apparent, then that information could be used to type the particular > usage of the word and the nature of the concept that goes along with > it. Once the program forms a better idea of how the term, 'captain' > can be used in a sentence, the better it can be used to determine how > the other words in the sentence are used. This reasonable insight > implies that words can have functional relationships with other words > and this is important because it provides evidence that word-meanings > can be typed. Word types are going to be involved in both semantic > and semantic-related syntactic relations that go way beyond the most > general types talked about in most modern grammatical analysis. For > example, some words may refer to a central subject of a comment while > others are directed toward other objects in the commentary. So the > idea that all the words in a comment should be treated as equal tokens > in some way is going to be insufficient. Similarly, words that are > only evaluated based on their co occurrences are not going to be > appropriately evaluated for their functional roles within a comment. > While attention to this has been paid in natural language analysis, it > has typically been done in such a way as to minimize the typing of the > words so that the analysis can apply to the broadest grammatical > types. And it always based on an elaborate, carefully designed model > and almost never as something the program has to discover. > > When I tried to think of some of the particular categories that the > word 'captain' could belong to I ran into more trouble than I expected > because my attempt to articulate those categorical types with precise > terms did not come easily. I am not claiming that we precisely define > the categories that words can belong to but that we can make little > fragmented stories about some of those meanings. Like 'the captain of > an airplane,' or 'the captain of a ship,' or 'a nickname we might give > the owner operator of a boat,' or 'a nominal leader amongst the > players of a team' and so on. > > The initial problem in linguistic analysis is discovering the intended > meaning of the terms used in a comment. So then, would this idea, > which is dependent on the discovery of a more narrow range of possible > meanings for a term, really help? I think it would because the > mechanisms of learning would be based on acquiring insight into these > associations and it could be done in a way that seems somewhat more > natural than establishing precisely defined grammatical categories. > > The typing of words and the functional power of words is different > than the distinct typing and functional-predicate relations of > specialized 'languages' like the operators of programming languages > and logical-computational languages. For example, each word is both a > type related to its usage in a comment and also a variable. Ignoring > the meaning of term 'predicate' in natural language grammar for a > second, I can say that a word can be both a predicate and an object of > the predicate because words are interactively functional with other > words. This is a very difficult computational 'language' and that is > why this theory has been effectively suppressed in NLP. > (Incidentally, this kind of theory can be reduced to a simpler > computational language for a precise interpretation of how a word is > used in a comment, but my whole argument is that until an AGI/AI > program can figure the meaning of a particular sentence fragment it > needs to deal with the more complicated system. My argument is: That > is just the way it is and until we deal with the reality there is very > little hope that we going to work it out.) > > But this process is not just limited to words, phrases and stories but > to all concepts. The idea behind conceptual typing is that the > interaction and functional roles of concepts are partially determined > by the typing of the concepts in a particular usage. Without dealing > intelligently with this problem in some manner it becomes less likely > that the dynamic interactions of concepts will be brought under > control to be used effectively. > > This system is unwieldy and at this time I cannot predict whether it > can be used effectively. However, one thing is clear; it must be > dependent on an extensive system of indexing. The problem of making > the most efficient indexing system seems to be NP-Complete. However, > by using an indexing system where the more frequently used paths are > given some preeminence in the indexing, along with the use of multiple > paths, it should be possible to create an effective indexing strategy. > - Jim Bromer ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
