Interpretations of a phrase and the production of a phrase can be based on
more than one motivating factor or more than one rule system (more than
one rule-like principle.)  So when new ideas are being examined, a simple
sentence might be used to indicate individual underlying principles that
can be used to understand the idea. But a more sophisticated form of
sentence might be used to indicate that the idea can be applied or analyzed
in different ways. This is a simple example of conceptual integration. I am
trying to say that the idea of regular strings, context-free strings and
context-sensitive strings can be applied to this theory of learning as
methods and as metaphors.

Jim Bromer


On Mon, Apr 7, 2014 at 9:38 AM, Jim Bromer <[email protected]> wrote:

> I have spent about 12 hours on my AI / AGI project so far this year, so I
> decided to end my self-imposed ban from the group since participating in
> this group seems to motivate me to work on my project.
>
> I think that I can use language to instruct an AI program to learn about
> the things that I can communicate through language. The program would be
> able to pick up factoids via simple language (similar to regular strings
> and context-free strings) but it would also be able to try to utilize
> knowledge and to acquire more insight through more complicated language
> (similar to context-sensitive strings). For example, (an abstract example),
> if it was trying to understand something that did not conform to some facts
> that it was familiar with (using higher level sentential structures that it
> was familiar with) it could use progressively more simple sentences to try
> to fit the new facts into the knowledge that it had previously acquired.
> Since I would be able to detect this, I, (as programmer-teacher), should be
> able to be able to make a good guess about the kind of knowledge that
> it might use effectively at that point.
>
> One problem is that word-concepts may change, not only in their
> application but in the level of abstraction and particularization. A word
> or a phrase can even be both more particular and more general at the same
> time. An exemplar is an example of this. For a program to benefit from this
> kind of abstraction-generalization polymorphism (many shapes-not OOP
> polymorphism) it has to be capable of both context-free (like)
> communication and context-sensitive (like) communication. It has to be able
> to plug new ideas into preexisting knowledge in simple ways, but then it
> has to try to derive some guesses about these new ideas in more
> sophisticated ways.
>
> This is a very simple explanation of how my program should work. I feel
> that AGI has failed just because knowledge is too complicated. But, I want
> to show that a basic strategy which includes the kind of thing that I
> mentioned here makes sense and it should work - at least until the
> knowledge base becomes too complicated.
> Jim Bromer
>



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