I think I started wondering why the two women were acting the way they were because the level of the attention that they were showing me at that moment was unexpected. If it had just been the unmarried women I would have guessed that she was wanted to strengthen our office friendship for some reason but because the married woman acted in a similar way I figured that there was some reason for their behavior that I was not aware of. I did make a systematic search through a few possibilities but I quickly came up with an explanation and I was able to check it out by making a few inquiring remarks. On the other hand, the question of how an AGI program might reason about hidden or more inscrutable problems requires a more extensive systematic search through the possibilities. The only thing that is keeping me from making a more extensive search is my lack of rationally insightful imagination to deal effectively with the problem.
Here is another example of an AGI problem. The first step of reacting to a situation is to recognize it. If the program was given the best guesses (the best rationally directed guesses) then it could choose from them based on previous learning. However, the problem is that finding the best guesses - even when it had extensive previous learning from examples - is elusive because there are so many possibilities to consider. There is no magic bullet that can take pixel data (for example) and reliably recognize it (as an image of something). If the program could go through all the possibilities (to give a familiar example of a possible solution) then it could pick out the best possibility. AI programs can do that as long as the number of possibilities are limited. But when there are too many possibilities then those kinds of systems just do not work fast enough. So a programmer might look at the context of a situation and try to break it down into parts. (That is another example by the way.) The problem here is that there are few one-to-one correspondences between 'parts' of a situation (or context) and a method that would interpret that part correctly. Here is an example of that situation. Suppose that you see a number of green pixels in an image. Does that mean that it is a picture of a leaf of some kind. The simple answer is no. There are few one-to-one correspondences between elemental sensory data events and 'meaning' or reference. If there were, computers would be really really good at it. This means that even good AGI methods will lead to complications. Some people do not understand this but if it weren't for AGI complexity we would already have strong AGI. Jim Bromer On Tue, Feb 5, 2013 at 5:25 AM, Mike Tintner <[email protected]>wrote: > You’ve given two examples of real world problems – “what do those women > really think about me?” / “how to reason about methods of dealing with > ‘inscrutable’ problems”? > > Show how in either (or any real world problem whatsoever) there is or can > be “ a systematic search through possibilities” > > What are the systematic possibilities whenever you have to “read minds” > (as above) – a classification which embraces a vast amount of > psychological RWR. > > What are the systematic possibilities for considering/reading – *what > Obama really intends to do in any foreign policy area”, or Iran intends to > do re Israel, or ......etc > > The whole damn point of RWR is that you don’t have a set of options – you > have to construct options from scratch – and you aren’t going to get > anywhere near a set. What you’re arguing is pretty well the complete > opposite of the truth. > > *From:* Jim Bromer <[email protected]> > *Sent:* Tuesday, February 05, 2013 10:05 AM > *To:* AGI <[email protected]> > *Subject:* Re: [agi] Multiple Vantages Can Be Used to Find Multiple > Observation Objectives > > Mike, lt is a systematic search through possibilities. The > possibilities are limited to reasoned conjectures about the problem. The > preparation does involve using ideas that had been considered before but > the majority of the ideas do not come from a pre-prepared set of > "options". The conjectures do include what I call imaginative projection, > but the use of the imagination in reasoned conjectures is driven by > rational consideration. > Jim Bromer > > > On Tue, Feb 5, 2013 at 4:51 AM, Mike Tintner <[email protected]>wrote: > >> Jim, My post explicitly said that a/your guess is a “reasoned >> inference.” The key point I’m making – and you’re ignoring – is that it’s a >> one-off, one-at-a-time business rather than a narrow AI systematic search >> through a pre-prepared set of options (the kind that cause such >> “complexity”). And this BTW is the irrefutable truth – no one’s going to >> produce an AGI problem where there is a neat set of options. >> When you noted the existence of “inscrutable events” – (I would say >> “partly invisible events/objects”) – you were onto something big, taking a >> big step forward in your AGI thinking. When you started looking for >> “reliable” ways of solving problems about them – (trying basically to cling >> to the old narrow AI ways) – you took a big step back. Concentrate on the >> invisible nature of the subjects of real world problems. There is no >> reliable way to deal with them. You just gotta get stuck in and guess, or >> if you prefer “hypothesize”/”theorise”. >> > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/6952829-59a2eca5> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <http://www.listbox.com> > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/10561250-470149cf> | > 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
