I did not mean to be overly critical in my last email. I was just trying to be objective, to the best of my ability. A major underlying goal in discrete AI has been to look for a simple set of rules and discrete object types which could be used as a basis for all knowledge. I believe these goals were driven by a few historical events. The importance of arithmetic and logic, both of which could be derived from a relatively simple set of rules; the value of arithmetic to humankind which could be developed with a minimization of rules; and the severe constraints on computer technology in the old days. I think that the learned development of many rules may be achieved with modern computers but that presupposes that there is more than one level of abstraction. So my ideas about AI are based largely on discrete methods, but the abstractions of the system have to be acquired and learned alongside other kinds of knowledge (like facts and how-to stuff), and made to fit the knowledge that is learned. No one in this group talks this way about this stuff. Of course, a critic can say that is implicit in someone else's ideas - except for the stuff I am getting wrong. To put it a little more accurately, the necessity of acquiring 'abstractions' along with 'knowledge' 'endpoints' (so to speak) is implicit in many if not most AI theories. So how is mine original the critic might ask? This would be an example of a dismissive argument. My theory is my own because other people do not bother to talk about stuff like this. So it may not be startlingly 'original' but it is my own theory (it is not based on some white-paper or something that someone else has talked about in these groups. You can find theories about 'abstraction' but there is less around about the necessity of developing abstractions as knowledge is developed and even less that suggests that these relationships might be expressed mathematically - at least to some extent. While I am interested in developing a fast mathematical index into knowledge (based on discrete-based knowledge) I now believe that a great deal of meaning can be -learned- and baked into the mathematical indexing system. For example, mathematics does not have to be restricted to a narrowing process (that produces a single numerical result) but it can also be an expanding process (that produces a set of results that might be expressed numerically.) Again, a critic can take a dismissive attitude and might say, for example, that fuzzy logic or any number of weighted methods can do that! Ok, but I could defensively reply that I am interested in mathematical references to sets that could (in theory) (typically) be derived from the values. Radical originality is not one of my goals. However, individual uniqueness is, because I believe that individuality is needed to develop useful computational methods that have yet to be developed. There are many unique aspects of my theories and the challenge is to find the theories which can be made to function as a whole and to eventually develop computer programs that will show their usefulness in future AI and AGI programs. Jim Bromer
On Tue, Jun 4, 2019 at 6:07 PM <[email protected]> wrote: > Ok, sorry about that misunderstanding. > > You need to form the model of the of the working area of the a.i. , its > true for us all, but how you do it, is what makes what your doing original. > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > <https://agi.topicbox.com/groups/agi/T395236743964cb4b-M0c0dd3364303694d41da54b7> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T395236743964cb4b-M8984999a5040c2b43963b404 Delivery options: https://agi.topicbox.com/groups/agi/subscription
