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Path: sparky!uunet!stanford.edu!agate!ucbvax!CATTELL.PSYCH.UPENN.EDU!neuron-request From: neuron-request@CATTELL.PSYCH.UPENN.EDU ("Neuron-Digest Moderator") Newsgroups: comp.ai.neural-nets Subject: Neuron Digest V10 #19 (discussion + jobs) Message-ID: <25295.722189886@cattell.psych.upenn.edu> Date: 19 Nov 92 16:18:06 GMT Sender: daemon@ucbvax.BERKELEY.EDU Reply-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu> Distribution: world Organization: University of Pennsylvania Lines: 609 Neuron Digest Thursday, 19 Nov 1992 Volume 10 : Issue 19 Today's Topics: Re: Help on hybrid systems Stock Market Faculty position at NYU 4 research posts Research enquire FYI: Results of Physics of Computation Workshop Send submissions, questions, address maintenance, and requests for old issues to "neuron-request@cattell.psych.upenn.edu". The ftp archives are available from cattell.psych.upenn.edu (130.91.68.31). Back issues requested by mail will eventually be sent, but may take a while. ---------------------------------------------------------------------- Subject: Re: Help on hybrid systems From: Dave Cornforth <djc@Cs.Nott.AC.UK> Date: Fri, 13 Nov 92 10:55:40 +0000 Don't know much about your field, but here's my two cents worth... If you already have some firm rules which are sound, then why not use them directly in your system? If you have some decisions which are a bit more "wooley", then you could look at a neural network to cope with those. However, I would suggest you do some kind of statistical analysis on your data first. If you find that you have data which is roughly normally distributed and unimodal for each class, which you want to assign to different classes (or decisions), then you can't beat a Gaussian model Bayesian classifier. If the data is not normally distributed, or multi-modal, then you could look at "real" neural networks, but there are also some jolly good memory table-based classifiers which tend to be a lot quicker to train. Dave ------------------------------ Subject: Stock Market From: P.Refenes@cs.ucl.ac.uk Date: Fri, 13 Nov 92 10:04:10 +0000 I am afraid I have not followed this topic very closely, but here are some references of our own work in teh field: [1] Refenes A. N., Zapranis A., and Azema-Barac M., "Stock Ranking: Neural networks Versus Multiple linear Regression", Proc ICNN'93 San Francisco (submitted 1992). [2] Refenes A. N., et al "Currency Exchange rate prediction and Neural Network Design Strategies", Neural computing & Applications Journal, Vol 1, no. 1., (1993). [3] Refenes A. N., & Zaidi A., "Managing Exchange Rate Prediction Strategies with Neural Networks", Proc. Workshop on Neural Networks: techniques & Applications, Liverpool (Sept. 1992), also in Lisboa P. G., and Taylor M, "Neural Networks: techniques & Applications", Ellis Horwood (1992). [4] Refenes A. N., & Azema-Barac M., "Neural Networks for Tactical Asset Allocation in the Global Bonds Markets", Proc. IEE Third International Conference on ANNS, Brighton 1993 (submitted 1992). [5] Refenes A. N. et al "Financial Modelling using Neural Networks", in Liddell H. (ed) "Commercial Parallel Processing", Unicom, (to appear). ------------------------------ Subject: Faculty position at NYU From: ltm@cns.nyu.edu (Laurence T. Maloney) Date: Sun, 15 Nov 92 20:02:07 -0500 N N Y Y U U * NN N Y Y U U * * * N N N Y U U * * * N NN Y U U * N N Y U U U JOB OPPORTUNITY TENURED OR TENURE-TRACK COGNITIVE SCIENCE/COGNITIVE PSYCHOLOGY/COGNITIVE NEUROSCIENCE -- NEW YORK UNIVERSITY: The Department of Psychology, Faculty of Arts and Science, New York University anticipates making faculty appointments beginning September 1993, in one or more of the above areas. These are tenured or tenure-track position and the rank is open. Candidates must be engaged in an active research program at the forefront of modern cognitive psychology, cognitive science, or cognitive neuroscience. Senior applicants should submit a vita. Others should also include reprints of recent publications and three letters of reference. Applications should be sent to Professor Murray Glanzer, Department of Psychology, 6 Washington Place, Room 965. TO ENSURE CONSIDERATION, APPLICATIONS SHOULD BE RECEIVED BY JANUARY 15, 1993. New York University is an Equal Opportunity/Affirmative Action Employer. Brief questions? E-mail to Larry Maloney, ltm@cns.nyu.edu. ------------------------------ Subject: 4 research posts From: Noel Sharkey <N.E.Sharkey@dcs.ex.ac.uk> Date: Mon, 16 Nov 92 11:36:21 +0000 Research Posts at Centre for Connection Science Department of Computer Science University of Exeter UK Four new research posts will be available (expected start January 1st, 1993) at the Centre for Connection Science, Department of Computer Science, as part of a 3-year research project funded by the SERC/DTI and led by Noel Sharkey and Derek Partridge. The project will investigate the reliability of software systems implemented as neural nets using the multiversion programming strategy. Two of the posts will at the post-doctoral level (grade 1A). The ideal applicant will be proficient in both neural computing and software engineering (although training in one or the other may be given). In addition, there is a requirement for at least one of the successful applicants to work on the formal analysis of network implementation as a paradigm for reliable software. The other two posts will be for Research Assistants/Experimental Officers at grade 1b. One of these will be required to have a high level of proficiency in C programming and general computing skills. The other will be part-time, and preference will be given to an applicant with good mathematical and engineering skills (particulary control systems). For more information please contact Lyn Shackelton by email (lyn@dcs.ex.ac.uk or by telephone (0392-264066 mornings 10.00-2.00). ------------------------------ Subject: Research enquire From: LHOTAK@whmain.east-london.ac.uk Date: 18 Nov 92 18:29:57 +0000 Dear reader, My name is Martin Lhotak and I currenly became a PhD. student at the University of East London. The topic of my PhD concerns with a model of an artificial intellect based upon classification paradigm and self- organizing hierarchy establishment and a short proposal summary of my PhD. topic follows: =< Start of my PhD. proposal>=================================== Title: A model of an artificial intellect based upon classification paradigm and self-organizing hierarchy establishment The PhD. research would investigate the principles of human intellect and the generic intellectual processes in systems leading to qualified understanding of the world the system is based in. Current achievements in this area have recorded just a partial success due to the approach to modell the intellectual process by large amount of rules, data, formulas,etc., which tends to be valid only under specific conditions. In my understanding those attributes (facts, data, formulas) do not represent intelligence, but only support and monitor the development process of a given intellect. In my PhD research I would like to look at the aforementioned process from the point of view of how the organization of a system changes during the information gathering process and how significant it is to gather information from various independent (often contradictory) sources. Especially, I would like to focus on the essential principles, e.g. classification and hierarchization, which, I believe, helps human intellect to cope with complex tasks. Based upon the theory of object classification and the results observed from the general information gathering process I would like to compose a prototype of an adaptive intelligent system capable of autonomous classification and autonomous establishment of hierarchies in order to "understand" the meanings of given "model world" objects. The theoretical model would require continuous testing on a given set of subject domains, e.g. Plant Fossil Record - a large heterogeneous data set, etc. ==< End of my proposal >======================================== As you have quite likely observed my PhD. topic is rather generous (and perhaps too ambitious) and it is highly probable that I would be more specific on the PhD. registration form after I would do some preliminary research. I realize that the aforementioned proposal is fairly vague and "nothing-specific-saying", however, some essential ideas should be visible and I would be very grateful for any (especially critical) comments on my approach or proposal for my PhD. studies and any information whether anyone has tried (or rejected) similar approach or whether anyone is already doing similar research in this area. I would be also very thankful for any possibility of consulting and discussing my ideas directly, via e-mail, or in a sort of a larger scientific arena (listservers?, meetings?). The best way how to contact me is via e-mail: lhotak@whmain.uel.ac.uk Best Regards, o #/- Martin Lhotak # \-/| #/-\ | ==============================================================# \-/ Martin Lhotak # eMail: lhotak@whmain.uel.ac.uk # Systems & Computing # sMail: 39, Lodge Avenue # University of East London # Dagenham, RM8 2JD # United Kingdom # telNo: 081-590-7722 ext. 4101 # =============================================================== ------------------------------ Subject: FYI: Results of Physics of Computation Workshop From: Doug Matzke <matzke@hc.ti.com> Date: Thu, 12 Nov 92 19:12:54 -0600 Hello The Physics of Computation Workshop was held on October 2-4, 1992 in Dallas Texas, and was attended by almost 100 people from industry, press, university, and government agencies. The attendees decided to: 1) Publish a post-proceedings of the papers with IEEE Press (see order form below to reserve you own copy - about 500 pages) 2) Start an electronic mailing list on the physics of computation. (Please send requests to physics.computation-request@hc.ti.com) 3) Have the next conference in two years. 4) Start publishing general articles to establish the field. One of the attendees is a science writer for the Dallas Morning News, and the text of his article is included to give you some sense of what happened at the workshop. So get involved with this emerging field by signing up with the mailing list, ordering your own copy of the post-proceedings, and making plans to attend the next conference. Doug Matzke Workshop Chairman EMAIL: matzke@hc.ti.com PHONE: (214) 995-0787 ********************************************************************* Order information for Post-Proceedings for Physics of Computation Workshop (Held on October 2-4, 1992 Dallas Texas) These post-proceedings are available at the prepublication rate of $35 (US Dollars), if your order is received by December 14, 1992, along with this form. If you order at the the conference rate, the book will be mailed to you directly from the printer. The Post-Proceedings will be available for purchase after publication, from the IEEE Computer Society Press, probably at a higher cost. NAME: ________________________________________________________________ ADDRESS:______________________________________________________________ CITY:___________________________________________ STATE:_______________ COUNTRY: _____________________________________ ZIPCODE:_______________ COPIES: ______________ X $35.00 = TOTAL AMOUNT: ______________________ Include check or money order for the full amount, made out to: Dallas IEEE Computer Society (No credit cards or COD, please.) Send this Completed form with check or money order to: Douglas Matzke Post-Proceedings Order for PCW Texas Instruments P.O. BOX 655474, MS 446 Dallas, Tx 75265 Questions may be directed to Doug at (214)995-0787 or matzke@hc.ti.com ********************************************************************* As appeared in Dallas Morning News Monday October 26, 1992 OPENING THE DOOR TO COMPUTER PHYSICS New field may solve mysteries about universe, time, genes By Tom Siegfried Some physicists can't get their minds off computers. Perhaps that's because minds seem to work a lot like like computers. Understanding the physics of how computers compute, some scientists reason, might provide clues to how brains do it, too. And even if it can't explain the the brain, the physics of computing may solve mysteries about the universe, the genetic code and why time always flows in one direction. At least those were among the topics discussed this month when researchers from around the world met in Addison to explore links between basic physical laws and the process of computation. Nearly 100 researchers from physics, computer science, mathematics and related fields shared insights on computers, quantum physics, black holes and the brain. Some speakers discussed using information theory to study problems in molecular biology or the working of human memory. Others showed how quantum theory can be used to devise better secret codes. Some speakers even described real physics in real computers. After all, Texas Instruments Inc. of Dallas sponsored the conference. At one level, studying the physics of computing does have a practical aspect. Knowing basic physics is critical in designing smaller, faster computer chips that won't melt down by producing too much heat. But speakers at the Addison meeting often focused on more theoretical questions, ranging from how to design a foolproof code for automates teller bank cards to whether the universe is a gigantic computer simulation. The diversity of the discussions suggested that while a new scientific discipline has been born, it's too soon for a christening. The new field is related to information theory, computer science, artificial intelligence, chaos and fractals, but it doesn't really have a name of its own. "It's clear that this field is not well defined," said Tommaso Toffoli of the computer science labaratory at the Massachusetts Institute of Technology. Researchers addressing this identity crisis could only conclude that the new field concerns itself with "fundamental connections between physics and computation." At the heart of this connection is an obscure but important rule called the Landauer principle. It involves how much energy a computation requires. More than three decades ago, IBM computer physicist Rolf Landauer calculated the least amount of energy needed to perform a single computational step. The answer, he showed, is essentially zero. If a computation is performed slowly eneough, the amount of energy used up can be as small as desired. That was a surprising result. Transferring information in a computer is like sending a message from one memory location to another, and physicists used to think that sending messages required energy. But the early studies took too limited a view of information transfer, usually considering signals sent by waves. "We don't have to send information by waves," said Dr. Landauer. "I can send you a floppy disk. If I'm desperate I can use the U.S. Postal Service." But even in computers, there's no free lunch. The catch is that computers have limited memories, so information has to be erased from time to time. And the Landauer principle, published in 1961, states that erasing information must use some minimum amount of energy. "Discarding information involves an unavoidable energy penality," Dr Landauer said at the Addison meeting. Landauer's principle places a theoretical limit on how energy-efficient a computer can possibly be. The principle doesn't matter much for today's real-life computers, which use much more energy than the theoretical minimum. But the principle came into play in numerous presentations at the Addison meeting, on topics ranging from black holes to the brain. For example, Christopher Fuchs of the University of North Carolina at Chapel Hill analyzed a peculiar method of erasing information with a black hole, a region of space around the remains of a collapsed star. Since the gravity of a black hole is too strong to permit anything within it to escape, a bit of information dropped into a black hole is lost forever. Does Landauer's principle apply when the information eraser is a black hole? Dr. Fuchs thinks so. A black hole swallowing a bit of information should grow in surface area, and Dr. Fuchs calculated that the amount of growth is roughly what would be expected if Landauer's principle is obeyed. David Wolpert, of the Santa Fe Institute in New Mexico, invoked Landauer's principle in explaining why the brain can only remember the past - unlike King Arthur's pal Merlin the Magician, who remembered the future. Dr. Wolpert tried to show how the psychological sense of time's one-way flow is related to the direction of time that arises from the second law of thermodynamics. Several speakers at the meeting discussed that law, which says, in essence, that disorder wins out over order. In other words, an organized system left to itself, will become disorganized. As time goes forward, eggs break but don't reassemble, building decay and machines wear out. The second law is widely regarded as among the most significant laws of physics. But it turns out that Landauer's principle is needed to save the second law from a demonic paradox. The Scottish physicist James Clerk Maxwell proposed the paradox in 1871. More than a century passed before work by Dr. Landauer and IBM colleague Charles Bennet explained it. Maxwell considered the effects of the second law in systems where something hot is separated from something cold. Open a door between a warm room and a cold room, and soon the air molecules will mix and both rooms will be the same temperature. The second law requires the mixing to create maximum disorder, or entropy. But Maxwell imagined a demon guarding the door between the rooms, opening it to allow the fast, hotter molecules into one room and closing it to keep the cold, slow molecules in the other. The demon could thus keep the rooms at different temperatures, an apparent violation of the second law. Physicists long supposed that the demon needed energy to observe the molecules and record information about their speed. The demon's energy use would create more disorder than the order he created, saving the second law. But, as Drs. Bennet and Landauer showed, computing the speeds of the molecules can be accomplished without using energy. Only when the demon resets his computer to calculate the speed of the next molecule is energy consumed, producing entropy to enforce the second law. Still, some physicists continue to wonder whether a sufficiently smart demon can outwit Dr. Landauer. Computer simulations to test new demon strategies were reported at the meeting by Andrew Rex and Ross Larsen of the University of Puget Sound in Tacoma, Wash. While the second law is still presumed to be safe, there is a way around Dr. Landauer's limit in computing - if a computer saves every intermediate result of every computation. Such a computer could then reverse every step, return to its starting place after carrying out a computation with no net use of energy, as Dr. Bennet demonstrated in 1973. But any computer keeping track of everything would need a huge memory. Ultimately, the size of such a computer would be limited by the size of the universe , Dr. Landauer pointed out. "The size of the memory is probably limited in principle, and not just by the size of your NSF (National Science Foundation) budget," he said. Of course, nobody would really try to build a computer the size of the universe. On the other hand, maybe somebody has. said Edward Fredkin of Boston University. He contends that the entire universe is just one big computer simulation. Physics, Dr. Fredkin asserts, is the constant processing of information to convert a representation of the present into a representation of the future. "Life works like a computer, thinking works like a computer and maybe physics works like a computer," he said. Whoever built this computer is not of our universe, of course. We're in the position of a pilot trainee flying from New York to Houston on a computerized 747 simulator. The computer is not in New York or Houston, but somewhere else. In the same way, says Dr. Fredkin, we live in a simulated universe running on a computer that is somewhere else. Dr. Fredkin's view isn't widely accepted. "I don't buy it," said physicist William Frensley of the University of Texas at Dallas. "I don't know if it's true or not," said physicist Seth Lloyd of Los Alamos National Laboratory in New Mexico. "I certainly doubt it's true in the sense that he (Dr. Fredkin) seems to think about it." Other speakers at the conference applied lessons from physics and computation to the mysteries of biology. Some presentations dealt with the best-known information storage system in biology - DNA, the molecule that makes up genes. DNA's genetic information is copied by RNA molecules in a cell's nucelus. The genetic information encoded in RNA molecules must then be cut up and spiced together before cells can use that information to make proteins. Thomas Schneider of the National Cancer Institute's mathenatical biology laboratory in Fredrick, Md., reported studies using information theory to understand how cells know when and where to splice. Several researchers tried to relate computational insights to the working of the human brain. Some discussed how brains represent information as patterns, others suggested ways that quantum physics could be involved in consciousness. Ordinarily, quantum physics describes the subatomic world where waves can be particles and particles can be waves, depending on how an experiment is set up. But whether quantum physics really has anything to do with consciousness is still speculation. And schemes for using curious effects of quantum physics in computing won't be showing up for sale at the Incredible Universe anytime soon. Dr. Lloyd pointed out thar quantum systems could in principle perform computations, but doing so in practice would be difficult or impossible. One quantum computing scheme, discussed by Richard Jozsa of the University of Montreal, could in theory compute complicated problems twice as fast as a standard computer. But you would only have a 50-50 chance of getting the answer to the question you asked. "You can get Two computations for the price of one, but only half of the time"," Dr. Jozsa said. Several speakers described one potential practical use for quantum physics - sending secret codes. Because quantum waves are disturbed by observation, efforts by an eavesdropper to detect a secret message can easily be detected. And an elaborate setup for sending and recieving quantum information can guarantee the ability to transmit a code no eavesdropper could possibly intercept. Claude Crepeau of the Ecole Normale Superieure in Paris suggested that the quantum coding scheme could be put to use in a bank card for use by automated teller machines. The system could be set up so that the password needed to use the card would be a perfect secret - nobody at the bank would even need to know the password. ************************************************************************ Extra box with caption Landauer's Principle vs. Maxwell's Demon Scientists have gained insights into the basic physics involved in computing -- or processing information -- by studying the connections betweeen computing and the second law of thermodynamics. That law syas that a natural system always tends to become more disordered as time passes, unless energy is imported from the system. No one has ever discovered a violation of this law. But in 1871, the scottish physicist James Clerk Maxwell proposed a paradox suggesting that a clever being, or "demon", might overcome the second law's requirements. Maxwell envisioned two chambers, one with hot air and one with cold air. According to the second law, opening the door between the chambers should cause the air molecules to mix, and bring both compartments to the same temperature. But Maxwell suggested that a demon guarding the door could open and close it selectively allowing the fast, hotter molecules to collect on one side and keeping the slow, colder molecules on the other side -- an apparent violation of the second law. Physicists long supposed that the demon needed to import energy to observe the molecules and calculate the necessary information about their speed. The use of imported energy would generate diorder outside the system to compensate for the order created inside, maintaining the requirements of the second law. But in recent years, studies by Rolf Landauer and Charles Bennet of IBM have shown that copmuting the speeds fo the molecules can be accomplished without using energy. But when the demon resets his computer to calculate the speed of the next molecule, energy is consumed, saving the second law. The notion that discarding information requires the use of energy, known as Landauer's principle, is a central consideration in a wide range of current investigations about the physics of computing. ------------------------------ End of Neuron Digest [Volume 10 Issue 19] *****************************************