On Monday 11 June 2007 09:47:38 pm James Ratcliff wrote: > > "J Storrs Hall, PhD" <[EMAIL PROTECTED]> wrote: On Monday 11 June 2007 08:12:08 pm James Ratcliff wrote: > > 1. Is anyone taking an approach to AGI without the use of Symbol Grounding? > > You'll have to go into that a bit more for me please.
Here's how Harnad defines it in his original paper: " My own example of the symbol grounding problem has two versions, one difficult, and one, I think, impossible. The difficult version is: Suppose you had to learn Chinese as a second language and the only source of information you had was a Chinese/Chinese dictionary. The trip through the dictionary would amount to a merry-go-round, passing endlessly from one meaningless symbol or symbol-string (the definientes) to another (the definienda), never coming to a halt on what anything meant. The only reason cryptologists of ancient languages and secret codes seem to be able to successfully accomplish something very like this is that their efforts are grounded in a first language and in real world experience and knowledge. The second variant of the Dictionary-Go-Round, however, goes far beyond the conceivable resources of cryptology: Suppose you had to learn Chinese as a first language and the only source of information you had was a Chinese/Chinese dictionary! This is more like the actual task faced by a purely symbolic model of the mind: How can you ever get off the symbol/symbol merry-go-round? How is symbol meaning to be grounded in something other than just more meaningless symbols? This is the symbol grounding problem." The reason this doesn't apply to AI the way philosophers tend to think it does is that there is a difference between a dictionary and a computer (or any other working machine): the computer has *mechanism* which can act out semantic primitives *by itself*. Thus the recursive construction of meaning does have a terminating base case. > > ... There's a whole raft of > philosophical conundrums (qualia among them) that simply evaporate if you take the systems approach to AI and say "we're going to build a machine that does this kind of thing, and we're going to assume that the human brain is such a machine as well." > > In what way? I try to edge around most of the fuzzy, magic points of philosophy and just get to what needs to be programmed. Good -- that's exactly what I was urging. DON'T try to get into the philosophical end of it -- you'll argue for 3000 years and come to no useful conclusions. > On the other hand, the trend to building robots in AI can be a valuable tool to keep oneself from doing the hard part of the problem in preparing the input for the program, thus fooling oneself into thinking the program has solved a harder problem than it has. > > What is the "hard part of the problem in preparing the input for the program"? Forall u: place(u) implies can(monkey, move(monkey, box, u)) can(monkey, climbs(monkey,box)) place(under(bananas)) at(box, under(bananas)) and on(monkey, box) implies can(monkey, reach(monkey, bananas)) Forall p forall x: reach(p,x) implies cause(has(p,x)) etc. The "feet of clay" stage is to put this problem into a computer in symbolic predicate logic. The hard part is going from a video/audio stream that would represent the monkey's experience to the rules that represent the monkey's model of how the world works. Josh ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=e9e40a7e
