Emahn, I am not talking about a fully authentic AGI but something more like a general AI program that could do some genuine learning. Most AI programs are capable of doing some kind of learning within a relatively narrow range. So when I talk about some genuine learning I am talking about the ability for a computer program to learn something that is new and is not presented in a narrow way like a combination of input values which are intended to be treated in one predefined way. (The issue becomes subtle since any computer program is going to react to input values in a predefined way so I am really talking about the ability for a computer program to adapt to input in a way so that it can learn something about meaningful input even if the input refers to something that was not fully predefined by some reference 'type' which conveys something significant about how the input semantics should be evaluated. Even this explanation is not subtle enough but it does at least convey my sense of the problem in that we are dealing with referential complications.)
As you say, this explanation of this 'glue of thought' as I called it might be based on hidden factors which could only be discovered by further study of early learning and other biological influences. And I would assume that there are many secrets that will only be discovered this way. But, as I was just thinking this morning, it might be explained by the use of other concepts which may seem mundane or unrelated to some particular subject. For example, the grammatical methods we use to direct someone's attention are not usually relevant to the subject that is being discussed but they are important kinds of actions that need to be used while discussing almost any subject. If our focus of study is always on the broad abstractions then we will usually try to understand the nature of some subject matter (as an abstraction) without looking at the details of how attention is drawn so that a reader or a listener might fit the pieces of what we are talking about together. (This is really interesting to me because it could even be encoded into formalized program and used as a simplified test. If I am right and the problem is one of referential complexity, then this formalized linguistic model could be used to test well structured referential complexity. A well-structured simplified model can be used to discover relevant problems when there are no more sophisticated methods immediately available. This idea of a formalized method to convey linguistic referential relations - especially referential complications - is like a golden parachute for me because if my current ideas about a prototype AGI program do not work out I could study something like this formal referential marker language. This formal language would not be just another programming language. Although it would not be an AGI program itself it might be able to convey some of the relations of an AGI simulation to a computer - if my sense that the central problem is a problem of referential complexity is right.) So I am really thinking about this from a practical point of view. How do we get a contemporary computer program to do some genuine learning where the referential markers of input are not fully detailed relative to some minimal comprehension goal. Jim Bromer On Sun, Oct 13, 2013 at 3:27 AM, Emahn Novid <[email protected]> wrote: > Wouldn't the (complexity behind the complexity idea) be highly dependent on > a parental figure/organization which would be the baby mind's only input of > logical associatons, with which the baby would build meaningful structure of > thought from? Especially since human babies take so long to both develop and > be able to survive independently compared to other animals. > > The parntal role would then bring us to a chicken and egg game looking down > our own evolutionary path to see where parental instincts developed from. > And when we take into account all l the hormonal/chemical reaction going on; > its clear that we most likely require significantly more biological > research. Without this additional scientific knowledge agi programmers would > lack the information needed to create a fully authentic type of agi, which > you are talking about. > > On Oct 12, 2013 8:44 AM, "Jim Bromer" <[email protected]> wrote: >> >> I think the problem of confirmation is one of the main problems. >> Complexity itself may be the real problem but it may just be that >> complexity makes the comprehension of what is going on or being said >> unreliable because the methods of confirmation are too crude to be >> used reliably in complicated situations. Because confirmation of >> some sort has to be used to build basic knowledge, the lack of robust >> methods to confirm theories means that general learning is quite >> difficult. The problem is that many little detailed pieces of >> knowledge are fundamental to even elementary theories about what is >> going on. If human beings could specify what those fundamental pieces >> of knowledge consisted of and how they help more substantial concepts >> interrelate then hand-crafted AI programs might stand as strong basis >> for further AGI design. But the lack of robust methods of >> confirmation means that many fundamental pieces of knowledge are still >> elusive. I could refer to these fundamental pieces of knowledge as >> structural knowledge but that might be a little misleading because my >> definition of structural knowledge goes beyond that. >> >> The use of imagination to develop theories and to then develop >> theories to confirm or disconfirm those theories will obviously lead >> to circular (or loopy) theories. This could serve to explain how >> human beings become stuck in ineffective strategies and can even >> become delusional but the problem is that our AGI efforts have not >> even reached the stage where meaningful delusion can be achieved. >> (Perhaps I could make the achievement of loopy delusional theories as >> an initial test of my AGI program – as long as the meaningful >> delusions are achieved in a system that used true general learning to >> reach that plain.) >> >> So, one of the major problems in a true AGI model, even one designed >> for limited feasibility tests, is that reliable methods of >> confirmation are elusive. But since true AGI has not really been >> achieved with supervised learning methods perhaps this problem might >> be better expressed as a problem of discovering the tiny theories that >> have to fill the interstices between the more well-illuminated >> theories that hold broader meaning. Perhaps it was a mistake to start >> by focusing on the broadest kind of knowledge that holds the strongest >> clues to comprehension and meaning. Maybe the secret formulas have >> been hidden in the trivial details all along. Perhaps there is a >> syntax of the glue of thought that explains how broader concepts can >> be held together. >> >> My feeling is that structural concepts hold the most promise to >> explain how knowledge may be advanced in an AGI program. If there is >> a glue to hold concepts together then that would definitely be called >> structural. Concepts play different roles when interacting with other >> concepts, just as some words are verbs some are nouns and so on. For >> me, a structural insight is one that is discovered when you realize >> that a combination of concepts (about words or events) can be >> understood by realizing how different concepts might be combined to >> make sense of the situation. >> >> The idea of conceptual structure has been used before my use of the >> idea to refer to the abstract rules that lay behind the application of >> some learned knowledge. For example, a logical deduction might be >> called structural learning. Or the programming behind a decision >> process might be called structural. But since I (and I assume a lot >> of other people) envision an AGI program where abstractions could be >> derived and learned by experience or by education that means that my >> idea of structural learning refers to concepts that can be learned or >> otherwise acquired as well. So then my idea of structural-concepts >> comes back to concepts that can hold a bunch of other concepts >> together in a conceptual complex by explaining the kinds of roles the >> concepts play in the complex. This understanding is definitely >> necessary for understanding. >> >> Jim Bromer >> >> >> ------------------------------------------- >> AGI >> Archives: https://www.listbox.com/member/archive/303/=now >> RSS Feed: https://www.listbox.com/member/archive/rss/303/24831508-4e7bc603 >> Modify Your Subscription: https://www.listbox.com/member/?&; >> Powered by Listbox: http://www.listbox.com > > AGI | Archives | Modify Your Subscription ------------------------------------------- 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
