Mike,
You didn't catch me, because you are wrong. And because I gave you many examples. I carefully document my examples and publish them in full. "Publish" means make them public, and you are part of the public. Detection, I would call attribution, it's like going back in causality. You too are a victim of the notion of problem. Your problems are scientific theorizing, detecting the cause of a disease, etc. You admit it, it is problemsolving. You say detection is a search, but it also needs logic. In my example, if I knew A, B and C, I would be perfectly satisfied. All of A, B, and C are true at the same time, so what? Well, I draw D from B and C, then I draw a conclusion from A and D (not named in the example), and that conclusion is that A and D are incompatible. That's where I know I need to search for more evidence. And I can draw conclusions from what I know, in a dynamical way, and use them as I go. And immediately learn something else (people came into the room) and draw some more conclusions. You are working with a static view, you want "all" information before you even start considering. The same mistakes Jim makes. Causal sets are a fantasy? FYI, we live in a causal world. You keep forgetting this, and I keep trying to remind you. Any theory or reasoning you carry out will be wrong if you ignore the facts. You never learn, you keep making the same mistakes. And blaming me for that. Sergio From: Mike Tintner [mailto:[email protected]] Sent: Saturday, September 01, 2012 11:59 AM To: AGI Subject: Re: [agi] Granularity Sergio:When we describe our world, we arbitrarily select the *granularity* of our description. (A) "The buttler is the assasin. He was at the scene, and he has a motive." That's a very coarse granularity, but it is already a causal set. Still, we can already take action. We can arrest the buttler and find more facts. (B) "The crime took place at 7:30." (C) "The buttler left the scene at 7:29." And we can draw a conclusion: (D) "The buttler was not at the scene at the time of the crime. We have now a better description, a finer granularity. But what does it mean to "draw a conclusion?" It means to *bind* or *associate* B and C to generate D. This is a logical step, and requires a mathematical logic operating on the causal set. Sergio, Gotcha, It’s hard to get examples of problemsolving out of you & others – but as soon as you do, one can get somewhere. You’re talking here about an example of an extremely broad class of real-world problemsolving – detection. Scientific theorising – incl. say when s.o. works out the cause of a disease – comes under detection. In detection, you have to work from evidence to detect hidden causes. Real world problemsolving, incl, detection, has absolutely nothing to do with logic. To suggest otherwise is naive. Real world problemsolving requires an extremely complex imaginative scenic knowledge of how actors and actions unfold in given scenes over time - a movie knowledge, not the sentential knowledge of language and logic. In this case, you have to know about people moving in and out of rooms, and (perhaps) how weapons are fired, and what kinds of weapons have what effects and much else – and all of this is imaginative – image-based. It is a total illusion to think that logic is involved - logic and language are merely sticking labels on the images - putting labels to movie/diagrammatic reasoning. Nothing happens without the movie/diagrammatic reasoning. You may only be aware consciously of reasoning with words and letters, but closer examination will show that massive imaginative reasoning underlies the surface. So if I say to you: “ok sure, he left the room at 7.29, but he could have gone round the back and fired in through the window at 7.30” where is your logic going to get you? How are A B C and D going to handle that? You have to be able to **imagine** the physical connection across a complex scene between evidence and cause - here between s.o. moving and running round the rooms, the house, the window, the position of the victim and so on – in order to agree or disagree with this argument. You have to **imaginatively reconstruct the scenes** .. “No that would have taken too long, surely... or he just might have managed it ... er why don’t we go and check?” You do indeed DRAW conclusions – by drawing lines across imaginative scenes between evidence and hypothetical causes – to see for example whether s.o. could have managed to run round, and whether s.o. outside the window could indeed have managed to hit the victim. The same principles apply to ALL scientific reasoning, ALL technological reasoning, - ALL real world reasoning. Your causal sets are a total fantasy when applied to **any** real world problem, (including BTW real world vision). An examination of the evidence of how scientists and others (including criminal detectives reason) will show that none of them use logic to DRAW conclusions. No one employs logicians for real world reasoning. An examination of all logical reasoning – by logicians – will also show no results that were of any direct use in real world reasoning. Logic produces only the most trivial of results. “Was the victim a man?” “Then he is mortal.” Thankyou and goodnight. Logic is blind – it cannot see any evidence. It cannot tell us anything new about the real world. Repeat: nothing new. Logic can only be used to explore the ramifications of a given set of known relationships between a given set of letters. It takes imaginative reasoning to make the connection between reasoning about artificial A’s, B’s, C’s and D’s – and physical events. Logic is utterly dependent on imaginative reasoning. And in real world reasoning, as distinct from logic, you can’t be sure what relationships do obtain. [“You say he was murdered – but it could have been a pre-arranged suicide”). So the only conclusion about the applicability of causal sets to real world reasoning, Sergio is -- back to the DRAWING board - of the imagination. From: Sergio Pissanetzky <mailto:[email protected]> Sent: Saturday, September 01, 2012 3:56 PM To: AGI <mailto:[email protected]> Subject: [agi] Granularity AGI, I don't recall having explained granularity on this blog before. My neglect has caused misunderstandings. So here it is. When we describe our world, we arbitrarily select the *granularity* of our description. (A) "The buttler is the assasin. He was at the scene, and he has a motive." That's a very coarse granularity, but it is already a causal set. Still, we can already take action. We can arrest the buttler and find more facts. (B) "The crime took place at 7:30." (C) "The buttler left the scene at 7:29." And we can draw a conclusion: (D) "The buttler was not at the scene at the time of the crime. We have now a better description, a finer granularity. But what does it mean to "draw a conclusion?" It means to *bind* or *associate* B and C to generate D. This is a logical step, and requires a mathematical logic operating on the causal set. The logic removes uncertainty from the causal set and creates structure. The set {B, C} is uncertain. We know B and C, but we ask "so what?" To reach D we have to remove the uncertainty. Removing uncertainty is easy for our brains. We don't even notice it happened because we are not aware of it happening. It is unconscious, and our brains do it all the time. You the reader can continue the excercise. Every bit of information we acquire is followed by a "remove uncertainty" step. Our brains are constantly removing uncertainty. AGI will never work unless we learn how to "remove uncertainty" on a computer. No adaptive system will work unless we learn how to "remove uncertainty" on a computer. Have courage, don't leave the uncertainty there. I must have tired everyone by saying entropy all the time. But entropy is just a measure of uncertainty. If someone is 6 feet tall, I must use "feet" to say that. Sergio AGI | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/6952829-59a2eca5> | <https://www.listbox.com/member/?&;> Modify Your Subscription <http://www.listbox.com> AGI | <https://www.listbox.com/member/archive/303/=now> Archives <https://www.listbox.com/member/archive/rss/303/18883996-f0d58d57> | <https://www.listbox.com/member/?&;> Modify 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-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
