Xref: utzoo comp.ai.philosophy:770 comp.ai.neural-nets:3098 Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!uupsi!sunic!news.funet.fi!polaris.utu.fi!magi From: magi@utu.fi (Marko Gronroos) Newsgroups: comp.ai.philosophy,comp.ai.neural-nets Subject: Re: Continuous vs. discrete Message-ID: Date: 26 Mar 91 01:28:53 GMT References: <91082.223501DOCTORJ@SLACVM.SLAC.STANFORD.EDU> <1991Mar25.141743.21124@news.larc.nasa.gov> Sender: usenet@polaris.utu.fi (Usenet News) Organization: University of Turku, Finland Lines: 80 In-Reply-To: kludge@grissom.larc.nasa.gov's message of 25 Mar 91 14:17:43 GMT This is a good subject! When they (the big names) 50 years ago worked out the principles of classical computers, they thought that they were creating something like the brain. And look what we got.. Binary logic circuits. Yak. The danger lies in optimization. When you optimize something, you gain something, and you lose something. The current trend in computer engineering seems to be optimizing. Everyone seems to have a tongue out for those new "neural circuits", but are they really so big step? They still are about exactly as digital and discrete in time and space as our current computers are (at least most of them in most aspects). > DOCTORJ@SLACVM.SLAC.STANFORD.EDU (Jon J Thaler) writes: ... >computers and brains is that (most) computers are finite state machines, >while it is not obvious to me that brains are. It is well known that >mathematical modelling of continuous systems on disctrete lattices >will miss some classes of solutions entirely, so I have trouble following >the arguments based on analogies between computers and brains. ... Yes, the problem seems to be that continuous systems are shitty (please forgive me the expression) to simulate with mathematics and even more difficult with classical computers. There are lots of good examples also in physics, like the multiple objects gravitational problem. If you make an algorithm that plays a game in a computer, you may lose a lot, even if you use a simpler neural network-method. It may be victorius against a human player, but so are conventional computer games. Intelligence doesn't mean efficiency; conventional computers are good in hacking numbers, and I am not, so why should I excpect my neural network to be good in hacking numbers. Nor does the intelligence necessarily require efficiency. Have you ever tried to play Ice Hockey on chessboard? There are 'men' on the chessboard, and they can move (with discrete time- and space-steps). There are strategies in ice hockey both on ice and chessboard, but they are very different. Also, there are about 10E100 different continuous physical things and 10E1000 skill-dependent and mental things in a game situation that affect a real ice hockey game, but none when two computers play this 'ice chess'. No one could recognize them as the same game.... kludge@grissom.larc.nasa.gov ( Scott Dorsey) said: > Maybe in the real world everything is discrete. For example, the current > flowing along a wire is not a continuous value, because it's actually the > flow of individual electrons, each with a fixed charge. Yes, but their arrival at the measuring point is quite continuous in time as well as is their position in the wire and possible effect (electric or magnetic field). > And since all > neurotransmitters consist of individual molecules, perhaps the brain is also > really a discrete system. Ehm.. No.. The electric fields around cells may have some effect in their functions, so the nerve cells may be discrete at only a very thin level between molecular movements and larger scale electrical behaviour. The problem with your idea is that you're only thinking about finite-state quantity, not time or space. That may also be a real problem in today's connectionism. Sorry for mixing the problems of algorithms to the finite-state-problem, but I think that they are quite similar in many ways. Both algorithms and finite-state-brains are much easier to think than the real world, and both lead to nothing in my opinion. Simplification of complex things is not always a good thing. More some other day. ----------------------------------------------------------------------------- Marko Gronroos ! Tel. +358-21-445613 ! Karvataskunkatu 10 H 100 ! ! Computer Scientists do it 20610 Turku ! ! with bigger hardware. Finland ! ! ----------------------------------------------------------------------------- Disclaimer: I wrote this late at night, which explains most of the mistakes. Try reading this late at night and you won't even notice my mistakes. Try appending this to your garbage pile before morning.