There are 2 approaches for programming AI: 1. Reductionist AI, in which the programmer hardwires a reductionist solution to a specific kind of problems. This approach is brittle when you change the kind of problems to solve. This is what Narrow AI is all about.
2. Holistic AI, in which the meta-programmer meta-programs a learning network capable of adapting its topology to fit the causal hyper-geometries of all kinds of problems. In other words, the Holistic AI system does the reduction process the programmer is supposed to do in the Narrow AI approach. This is what General AI is all about. Holistic AI is the approach of Monica Anderson and me. The book "Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World" is about Holistic AI. On Sun, Jun 30, 2013 at 8:34 AM, Jim Bromer <[email protected]> wrote: > > > ------------------------------ > Date: Sat, 29 Jun 2013 23:17:15 -0500 > Subject: [agi] Probably Approximately Correct: Nature's Algorithms for > Learning and Prospering in a Complex World [By Leslie Valiant] > From: [email protected] > To: [email protected] > > > Probably Approximately Correct: Nature's Algorithms for Learning and > Prospering in a Complex World [By Leslie Valiant] > http://www.amazon.com/dp/B00BE650IQ/ref=cm_sw_r_tw_ask_bQunF.0CDBG0V > > ------------------------------------------------------- > I am just guessing about what the book is about based on the blurb, but > the idea that we can muddle through without needing to understand what is > going on is either poorly stated or nonsense. Although our theories are > usually pretty weak, they are none the less theories. I do not believe > that we are just basing our interest according to a coincidental > correlation between three objects which can then be used to create chains > and fences of correlations. I believe that the imagination is extremely > important both in discovering objects of interest and in generating > theories to explain the mechanisms behind the objects. That does not mean > that we never rely on the linkages of ternary correlations it is just > that a computational explanation of consciousness which goes that since a > computer is not "conscious" of what it is doing then the potential for > higher computational intelligence must prove that human beings are not > "conscious" of what they are doing, just does not work for me. We are > conscious of some of what we do even if these theories are not very good > ones. > > One thing that I have been talking about for a number of years now is the > importance of structural integration of concepts. Even if our theories and > knowledge about a subject of interest are not that great we can begin to > develop different ways to think about the subject and then use these > different vantages to begin building better responsive insight about the > subject. I think this can be done in AGI programs. Weak theories do not > (always) need to be disposed but their influence in deriving conclusions > about a subject matter can be modified so that they are used when more > appropriate for the conditions. > > - This is only one possible presentation about my theories of structural > integration. This is one way that I have to think about the subject. > Parts of this presentation should seem very familiar to people who have > thought about the subject and I am sure that there are people who would > seize on the part where I said, the "influence [of weak theories] in > deriving conclusions about a subject matter are modified so that they can > be used when more appropriate for the conditions," as referring to the > exact same thing as they have thought about when they try to > design AI methods capable of producing improvement over time or after > training. However, this effort to interpret what someone else says only on > the basis of whether or not -I- have thought about things like this before > can produce extremely insipid conclusions. (I do it all the time so I am > not claiming some kind of superiority.) One reason my thoughts about this > subject are a little different than the typical machine learning paradigm > of learning-based improvement is that I explicitly emphasize the use of > theories during learning. I was not just talking about the theories > of people (who programmed some learning mechanism) but about the theories > that the AGI program might generate through artificial imagination. So, > had someone misread my statement believing that his machine learning theory > was already imbued with a system where, 'conclusions about a subject matter > were modified so that they would be used when more appropriate for the > conditions,' he might have missed the point of my message entirely. That > is one of the most serious problems with egomaniac-driven theorization. If > you read everything only in the terms of how it is right or wrong according > to your own theories you may end up missing central points of some > reasonable remarks. > > So even though computers may not be conscious like we are I believe that > we have to use meta-awareness in our AGI programs in order to make them act > more reasonably. The theories that they will generate may not be that > great but by using conceptual structural integration I believe that it > should be feasible for them to use imagination and reason to build better > analysis and response methods. So as they learn, some of their weak > theories will be strengthened by making them more conditional and by > extending their range of implementation slightly. This is only one part of > my structural integration theories. > > Jim Bromer > <http://www.listbox.com> > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/23601136-e0982844> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <http://www.listbox.com> > ------------------------------------------- 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
