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Received: from BUACCA by BUACCA.BU.EDU (Mailer R2.08 PTF009) with BSMTP id 6577; Fri, 19 Feb 93 01:31:27 EST Received: from noc2.dccs.upenn.edu by BUACCA.BU.EDU (IBM VM SMTP R1.2.1) with TCP; Fri, 19 Feb 93 01:31:24 EST Received: from CATTELL.PSYCH.UPENN.EDU by noc2.dccs.upenn.edu id AA16068; Fri, 19 Feb 93 01:28:48 -0500 Return-Path: <marvit@cattell.psych.upenn.edu> Received: from LOCALHOST by cattell.psych.upenn.edu id AA28888; Fri, 19 Feb 93 00:23:09 EST Posted-Date: Fri, 19 Feb 93 00:22:32 EST From: "Neuron-Digest Moderator" <neuron-request@cattell.psych.upenn.edu> To: Neuron-Distribution:; Subject: Neuron Digest V11 #12 (mailing lists & lots of discussion) Reply-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu> X-Errors-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu> Organization: University of Pennsylvania Date: Fri, 19 Feb 93 00:22:32 EST Message-Id: <28852.730099352@cattell.psych.upenn.edu> Sender: marvit@cattell.psych.upenn.edu Neuron Digest Friday, 19 Feb 1993 Volume 11 : Issue 12 Today's Topics: BIOSCI/bionet Frequently Asked Questions mailing list for cognitive neuroscientists NATO ASI: March 5 Deadline Approaching VLSI NN Re: "neural-net based software for digitization of maps" Applications for particle track segment detection?? Pattern Recognition Re: chip design neural net applications to fixed-income security markets Room sharing for ICNN pattern recognition (pratical database considerations) ? 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: BIOSCI/bionet Frequently Asked Questions From: Dave Kristofferson <kristoff@net.bio.net> [[ Editor's Note: This contains the information about the Neuroscience list which many of you readers have asked about. The entire file is about 48K long, so I've heavily edited the following with enough information about the Neuroscience list for you. If you (or colleagues) are biologically oriented (e.g., genetic sequencing, molecular biology, tropical ecology, etc), I highly recommend the BIOSCI/bionet resources. Consider browsing through the newsgroups or archives. -PM ]] BIOSCI/bionet Frequently Asked Questions (FAQ) ---------------------------------------------- (last revised - 1/15/93) This document describes the general purpose and uses of the BIOSCI/bionet newsgroups and provides details on how to participate in these forums. It is available for anonymous FTP from net.bio.net [134.172.2.69] in pub/BIOSCI/biosci.FAQ. This document may also be requested by e-mail to biosci@net.bio.net (use plain English - this is not a server address). It is posted the first of each month to the BIONEWS/bionet.announce newsgroup along with the BIOSCI information sheet and the list of changes to the newsgroups during the preceding month. The FAQ is also posted monthly to the USENET newsgroup news.answers and is archived along with other USENET newsgroup FAQs at pit-manager.mit.edu [18.172.1.27]. [[...]] Dissemination is by normal electronic mail and also over USENET in the form of the "bionet" newsgroups (see below for USENET details). The contents of the electronic mail distribution is identical to the USENET news distribution, but we encourage BIOSCI users to access the system through USENET news software whenever possible. E-mail distributions may eventually be phased out. As of October 1992, 59% of our readers used USENET news software instead of e-mail. [[...]] Two versions of the BIOSCI info sheet are available, one for the Americas and the Pacific Rim countries, and the second for Europe, Africa, and Central Asia. The former may be requested by e-mail to biosci@net.bio.net, while the latter may be requested from biosci@daresbury.ac.uk. [[...]] How do I request or cancel e-mail subscriptions to BIOSCI newsgroups? - --------------------------------------------------------------------- If you have access to USENET news software, then YOU DO NOT NEED AN E-MAIL SUBSCRIPTION! Only those people who need to receive postings by e-mail must request to be added to the mailing lists. USENET users can simply read the various bionet newsgroups using their news software. If your site has USENET news but does not get the bionet newsgroups, please request help by sending a message to biosci@net.bio.net. For those who need e-mail subscriptions or who want to cancel current e-mail subscriptions, please send a request to one of the following addresses. Please choose the site that serves your location. Simply pick the newsgroup(s) from the list above that you wish to subscribe to and request that your address be added to the chosen mailing lists. Please use plain English; no special message syntax is required in your subscription or cancellation request. Address Serving - ------- ------- biosci@net.bio.net The Americas and Pacific Rim biosci@daresbury.ac.uk Europe, Africa, and Central Asia ****If you are changing e-mail addresses****, please be sure to send a message to your appropriate biosci address above and request that your subscriptions be changed or canceled!! How can I get a list of newsgroups or my subscriptions? - ------------------------------------------------------- As with any other subscription correspondence, simply send a request to your appropriate BIOSCI distribution site: Address Serving - ------- ------- biosci@net.bio.net The Americas and Pacific Rim biosci@daresbury.ac.uk Europe, Africa, and Central Asia The most recent list of BIOSCI newsgroups/mailing addresses and the latest revision of the BIOSCI/bionet FAQ are posted the first of each month on the BIONEWS/bionet.announce newsgroup. You should save these postings for future reference. [[...]] MAILING LIST NAME USENET Newsgroup Name - ----------------- --------------------- AGEING bionet.molbio.ageing AGROFORESTRY bionet.agroforestry ARABIDOPSIS bionet.genome.arabidopsis BIOFORUM bionet.general BIO-INFORMATION-THEORY + bionet.info-theory BIONAUTS bionet.users.addresses BIONEWS ** bionet.announce BIO-JOURNALS bionet.journals.contents BIO-MATRIX bionet.molbio.bio-matrix BIO-SOFTWARE bionet.software CHROMOSOME-22 bionet.genome.chrom22 COMPUTATIONAL-BIOLOGY ** bionet.biology.computational EMBL-DATABANK bionet.molbio.embldatabank EMPLOYMENT bionet.jobs GDB bionet.molbio.gdb GENBANK-BB bionet.molbio.genbank GENETIC-LINKAGE bionet.molbio.gene-linkage HIV-MOLECULAR-BIOLOGY bionet.molbio.hiv HUMAN-GENOME-PROGRAM bionet.molbio.genome-program IMMUNOLOGY bionet.immunology JOURNAL-NOTES bionet.journals.note METHODS-AND-REAGENTS bionet.molbio.methds-reagnts MOLECULAR-EVOLUTION bionet.molbio.evolution NEUROSCIENCE bionet.neuroscience PLANT-BIOLOGY bionet.plants POPULATION-BIOLOGY bionet.population-bio PROTEIN-ANALYSIS bionet.molbio.proteins PROTEIN-CRYSTALLOGRAPHY bionet.xtallography SCIENCE-RESOURCES bionet.sci-resources TROPICAL-BIOLOGY bionet.biology.tropical VIROLOGY bionet.virology WOMEN-IN-BIOLOGY bionet.women-in-bio + full name is BIOLOGICAL-INFORMATION-THEORY-AND-CHOWDER-SOCIETY ** Note that newsgroups flagged with ** are moderated, i.e., postings are directed to a moderator (editor) who later forwards messages (possibly edited or condensed) to the newsgroup. NEWSGROUP NAME TOPIC - -------------- ----- AGEING Discussions about ageing research AGROFORESTRY Discussions about agroforestry research ARABIDOPSIS Newsgroup for the Arabidopsis Genome Project BIOFORUM Discussions about biological topics for which there is not yet a dedicated newsgroup BIOLOGICAL-INFORMATION- THEORY-AND-CHOWDER-SOCIETY Applications of information theory to biology BIONAUTS Question/answer forum for help using electronic networks, locating e-mail addresses, etc. BIONEWS ** General announcements of widespread interest to biologists BIO-JOURNALS Tables of Contents of biological journals BIO-MATRIX Applications of computers to biological databases BIO-SOFTWARE Information on software for the biological sciences CHROMOSOME-22 Mapping and Sequencing of Human Chromosome 22 COMPUTATIONAL-BIOLOGY ** Mathematical and computer applications in biology EMBL-DATABANK Messages to and from the EMBL database staff EMPLOYMENT Job opportunities GDB Messages to and from the Genome Data Bank staff GENBANK-BB Messages to and from the GenBank database staff GENETIC-LINKAGE Newsgroup for genetic linkage analysis HIV-MOLECULAR-BIOLOGY Discussions about the molecular biology of HIV HUMAN-GENOME-PROGRAM NIH-sponsored newsgroup on human genome issues IMMUNOLOGY Discussions about research in immunology JOURNAL-NOTES Practical advice on dealing with professional journals METHODS-AND-REAGENTS Requests for information and lab reagents MOLECULAR-EVOLUTION Discussions about research in molecular evolution NEUROSCIENCE Discussions about research in the neurosciences PLANT-BIOLOGY Discussions about research in plant biology POPULATION-BIOLOGY Discussions about research in population biology PROTEIN-ANALYSIS Discussions about research on proteins and messages for the PIR and SWISS-PROT databank staffs. PROTEIN-CRYSTALLOGRAPHY Discussion about crystallography of macromolecules and messages for the PDB staff SCIENCE-RESOURCES Information from/about scientific funding agencies TROPICAL-BIOLOGY Discussions about research in tropical biology VIROLOGY Discussions about research in virology WOMEN-IN-BIOLOGY Discussions about issues concerning women biologists ** Note that newsgroups flagged with ** are moderated, i.e., postings are directed to a moderator (editor) who later forwards messages (possibly edited or condensed) to the newsgroup. ------------------------------ Subject: mailing list for cognitive neuroscientists From: kpc@pluto.arc.nasa.gov (k p c) Organization: NASA Ames Research Center AI Research Branch; Sterling. Date: 27 Oct 92 01:26:08 +0000 [[ Editor's Note: Here is another mailing list of interest to some. I attempted to joi, but have received nothing. I sent a new message a couple of days ago, still without reply. I can therefore not personally vouch for this list's existance. -PM ]] ANNOUNCEMENT OF THE COGNEURO (COGNITIVE NEUROSCIENCE) MAILING LIST SUBJECT this list is an informal, intentionally low-volume way to discuss matters at the interface of cognitive science and neuroscience. the discussion will be scientific and academic, covering biological aspects of behavior and cognitive issues in neuroscience. also discussable are curricula, graduate programs, and jobs in the field. HOW TO USE THE LIST please follow these examples exactly, so that my software works. to SUBSCRIBE, send mail like this. To: cogneuro-request@ptolemy.arc.nasa.gov Subject: cogneuro: subscribe to UNSUBSCRIBE, send mail like this. To: cogneuro-request@ptolemy.arc.nasa.gov Subject: cogneuro: unsubscribe you don't need to put anything in the body of the message. there will be no automatic confirmation, but you might get a note from me. to CHANGE YOUR EMAIL ADDRESS (also very polite to do if you know that your MACHINE WILL GO DOWN for a while, or in case you LEAVE THE NET) simply unsubscribe from your old address and resubscribe from your new address. this prevents error messages and prevents me from having to verify your address manually. to POST (send a message to everybody on the list), send mail to cogneuro@ptolemy.arc.nasa.gov, or followup to an existing message. e.g. To: cogneuro@ptolemy.arc.nasa.gov Subject: corpus callosum to ask a METAQUESTION, send it to cogneuro-request@ptolemy.arc.nasa.gov. suggestions for improving this announcement or the list are welcome. GUIDELINES the language of the list is english. the list is meant to be low in volume and high in s/n ratio. since cogneuro is a huge field, submissions shouldn't be too off-topic or otherwise not essentially scientific or academic. controversy and speculation are welcome, as are lack of controversy and rigor. since the emphasis is scientific and academic, participants are expected to be extremely tolerant of other participants' opinions and choice of words. the list is initially open to anybody who is interested. although i don't expect ever to need to exercise it, i reserve the right to remove anybody from the list if there are problems. i want to keep a spirit of free exchange of cognitive neuroscience. other than this, the list is unmoderated and informal. ------------------------------ Subject: NATO ASI: March 5 Deadline Approaching From: John Moody <moody@chianti.cse.ogi.edu> Date: Thu, 04 Feb 93 17:38:08 -0800 As the March 5th application deadline is now four weeks away, I am posting this notice again. NATO Advanced Studies Institute (ASI) on Statistics and Neural Networks June 21 - July 2, 1993, Les Arcs, France Directors: Professor Vladimir Cherkassky, Department of Electrical Eng., University of Minnesota, Minneapolis, MN 55455, tel.(612)625-9597, fax (612)625- 4583, email cherkass@ee.umn.edu Professor Jerome H. Friedman, Statistics Department, Stanford University, Stanford, CA 94309 tel(415)723-9329, fax(415)926-3329, email jhf@playfair.stanford.edu Professor Harry Wechsler, Computer Science Department, George Mason University, Fairfax VA22030, tel(703)993-1533, fax(703)993-1521, email wechsler@gmuvax2.gmu.edu List of invited lecturers: I. Alexander, L. Almeida, A. Barron, A. Buja, E. Bienenstock, G. Carpenter, V. Cherkassky, T. Hastie, F. Fogelman, J. Friedman, H. Freeman, F. Girosi, S. Grossberg, J. Kittler, R. Lippmann, J. Moody, G. Palm, R. Tibshirani, H. Wechsler, C. Wellekens Objective, Agenda and Participants: Nonparametric estimation is a problem of fundamental importance for many applications involving pattern classification and discrimination. This problem has been addressed in Statistics, Pattern Recognition, Chaotic Systems Theory, and more recently in Artificial Neural Network (ANN) research. This ASI will bring together leading researchers from these fields to present an up-to-date review of the current state-of-the art, to identify fundamental concepts and trends for future development, to assess the relative advantages and limitations of statistical vs neural network techniques for various pattern recognition applications, and to develop a coherent framework for the joint study of Statistics and ANNs. Topics range from theoretical modeling and adaptive computational methods to empirical comparisons between statistical and neural network techniques. Lectures will be presented in a tutorial manner to benefit the participants of ASI. A two-week programme is planned, complete with lectures, industrial/government sessions, poster sessions and social events. It is expected that over seventy students (which can be researchers or practitioners at the post-graduate or graduate level) will attend, drawn from each NATO country and from Central and Eastern Europe. The proceedings of ASI will be published by Springer-Verlag. Applications: Applications for participation at the ASI are sought. Prospective students, industrial or government participants should send a brief statement of what they intend to accomplish and what form their participation would take. Each application should include a curriculum vitae, with a brief summary of relevant scientific or professional accomplishments, and a documented statement of financial need (if funds are applied for). Optionally, applications may include a one page summary for making a short presentation at the poster session. Poster presentations focusing on comparative evaluation of statistical and neural network methods and application studies are especially sought. For junior applicants, support letters from senior members of the professional community familiar with the applicant's work would strengthen the application. Prospective participants from Greece, Portugal and Turkey are especially encouraged to apply. Costs and Funding: The estimated cost of hotel accommodations and meals for the two-week duration of the ASI is US$1,600. In addition, participants from industry will be charged an industrial registration fee, not to exceed US$1,000. Participants representing industrial sponsors will be exempt from the fee. We intend to subsidize costs of participants to the maximum extent possible by available funding. Prospective participants should also seek support from their national scientific funding agencies. The agencies, such as the American NSF or the German DFG, may provide some ASI travel funds upon the recommendation of an ASI director. Additional funds exist for students from Greece, Portugal and Turkey. We are also seeking additional sponsorship of ASI. Every sponsor will be fully acknowledged at the ASI site as well as in the printed proceedings. Correspondence and Registration: Applications should be forwarded to Dr. Cherkassky at the above address. Applications arriving after March 5, 1993 may not be considered. All approved applicants will be informed of the exact registration arrangements. Informal email inquiries can be addressed to Dr. Cherkassky at nato_asi@ee.umn.edu ------------------------------ Subject: VLSI NN From: Gasser Auda <gasser@cs.uregina.ca> Date: Sat, 06 Feb 93 13:30:14 -0600 [[ Editor's Note: I'm starting to reject these vague general calls for help, due to the increased volume of submissions to the Digest. However, I don't want to shut out the rank beginners from this exciting field either. So, I hope faithful readers will take pity on those who are just starting out with some pointers. -PM ]] Dear neural networkers, I'm performing a survey on NN solutions of the handwriting problems, especialy VLSI implemented solutions. If you have any advise, information, paper, or commercial product, just email me at: gasser@cs.uregina.ca THANKS IN ADVANCE. gasser ------------------------------ Subject: Re: "neural-net based software for digitization of maps" From: eytan@dpt-info.u-strasbg.fr (Michel Eytan, LILoL) Date: Sun, 07 Feb 93 11:24:26 +0100 >A colleague from India is asking me if there is any effort on "neural >network based software for the digitization of maps and photos (maps and >photos presumably obtained from remotely-sensed data)" Is there any one >who can help answer this question? Thanks > >Rao Vemuri >Dept. of Applied Science >UC Davis, Livermore, CA >vemuri@icdc.llnl.gov My colleague J. Korczak <korczak@dpt-info.u-strasbg.fr> has a student, Ms. Hamadi, doing a Ph. D. on a similar subject. Hope this helps. Michel Eytan, U. Strasbourg II eytan@dpt-info.u-strasbg.fr Lab Info, Log & Lang, Dpt. Info V: +33 88 41 74 29 22 rue Descartes, 67084 Strasbourg F: +33 88 41 74 40 ------------------------------ Subject: Applications for particle track segment detection?? From: "Martin J. Dudziak" <DUDZIAK@vms.cis.pitt.edu> Date: Sun, 07 Feb 93 14:09:00 -0500 I am involved in a joint collaboration involving U-Pitt and the Institute of Nuclear Physics, Novosibirsk (Russia) wherein we are studying the possible useful applications of neural networks for particle track segment detection and track reconstruction. The process is now handled by some effective and well-established algorithms developed at CERN, Novosibirsk and elsewhere, but we believe that neural nets may have applicability for both improved detection (picking up on track segments registered in the drift chamber portion of the detector) and performance, particularly as the data rates in the detection process will be quite high (@40-100MBytes/sec.) in the next generation accelerator and we are working with a parallel processing architecture already to meet that computing requirement. We are aware of some work in the high energy physics community involving neural networks, most of which is more concerned with classification of particle interactions - the step that follows after one has identified tracks of interest. Much of that work has also not involved the low-level end of the detection process such as we are concerned about, nor has it involved the density of tracks. I thought it would be useful to inquire through the neural network community in grapevines such as Neuron-Digest to see if people are aware of projects applying neural nets to problems such as the above. Any information on NNs in HEP and for track detection/reconstruction in particular will be greatly appreciated. Whatever is sent will be compiled into a bibliography and redistributed to those who are interested. Martin Dudziak c/o J. Thompson, School of Physics, Univ. of Pittsburgh dudziak@vms.cis.pitt.edu Thank you! ------------------------------ Subject: Pattern Recognition From: VOGLINOG@AGR04.ST.IT Date: Mon, 08 Feb 93 11:47:55 +0700 [[ Editor's Note: Again, a rather general and vague request. Perhaps someone from Italy on this mailing list could help out a fellow countryperson? -PM ]] Hello. Where to get some software on pattern recognition based on neural network ? Thank you. GIuseppe Voglino SGS-Thomson Microelectronics Neural Network Group R&D Agrate B. _ MILAN - ITALY ------------------------------ Subject: Re: chip design From: blam@Engn.Uwindsor.Ca (B Lam) Date: Mon, 08 Feb 93 13:06:16 -0500 [[ Editor's Note: This plucky person rephrased his question from "Tell me about neural nets" to the follow (somewhat more specific) question... after I rejected his first attempt. My public reply to the specifics of his questio would be to look at Carver Mead's book (MIT Press?) "Analog VLSI" to start, but I don't know whether it covers fuzzy stuff. -PM ]] I'm looking the analog VLSI design for the Neural Network. I'm thinking to combine Fuzzy into NN. Is there any paper that talk about this topic? I'd look the journal of IEEE Tran. on NN but it seems to talk about the theory or software only. So please help me with this one. Thanks! ------------------------------ Subject: neural net applications to fixed-income security markets From: danlap@internet.sbi.com (Dan LaPushin) Date: Mon, 08 Feb 93 18:26:43 -0500 To The Editor, I am new to the field of neural networks but have a strong background in mathematics, economics, and some computer programming. I work at a large Wall St. firm and am interested in applying neural network technology to the field of fixed-income research. Such instruments include bonds, mortgage-backed securities and the like. There seems to be, as far as I can tell, little research into neural net application to such markets. I suspect this is because the data is hard to come by for those not in the field, but I'm not sure. Could you direct me to any research in this area so that I don't inadvertently recreate the wheel? Thanks for your help! Dan LaPushin I'm on your mailing list as danlap@sp_server.sbi.com ------------------------------ Subject: Room sharing for ICNN From: nanda@ogicse.cse.ogi.edu (Nandakishore Kambhatla) Organization: Oregon Graduate Institute (formerly OGC), Beaverton, OR Date: 10 Feb 93 18:02:30 +0000 Hi, I am a male graduate student attending ICNN'93 at SF. I am looking for roommates (1) to share a hotel room with at San Fransisco for ICNN'93. The conference runs from Mar 29th to April 1st. Please respond thru email in case you are interested. - -Nanda Nandakishore Kambhatla email: nanda@cse.ogi.edu phone: daytime-(503)-690-1121 (Extn-7051) evenings-(503)-646-5777 ------------------------------ Subject: pattern recognition (pratical database considerations) ? From: "Duane A. White" <KFRAMXX%TAIVM2.BITNET@TAIVM1.taiu.edu> Date: Sat, 13 Feb 93 03:45:41 -0600 I am interested in pattern recognition. In my particular application I would like to compare a 2D monochrome bitmap image with those in a database. The program should determine if there is a match, and if not then add it to the database. Most of the literature I've read on pattern matching networks use a relatively small set of classification patterns (such as letters of the alphabet, numbers). In my case it wouldn't seem practical to train a single network to identify every entry in the database (on the order of hundreds or thousands of entries). Is there something fundemental in the approach that I'm missing? Also the program should to a small degree be rotation and translation invariant. ------------------------------ End of Neuron Digest [Volume 11 Issue 12] ***************************************** Received: from BUACCA by BUACCA.BU.EDU (Mailer R2.08 PTF009) with BSMTP id 6666; Tue, 23 Feb 93 12:54:11 EST Received: from noc2.dccs.upenn.edu by BUACCA.BU.EDU (IBM VM SMTP R1.2.1) with TCP; Tue, 23 Feb 93 12:54:08 EST Received: from CATTELL.PSYCH.UPENN.EDU by noc2.dccs.upenn.edu id AA03416; Tue, 23 Feb 93 12:44:05 -0500 Return-Path: <marvit@cattell.psych.upenn.edu> Received: from LOCALHOST by cattell.psych.upenn.edu id AA04331; Tue, 23 Feb 93 10:57:09 EST Posted-Date: Tue, 23 Feb 93 10:56:33 EST From: "Neuron-Digest Moderator" <neuron-request@cattell.psych.upenn.edu> To: Neuron-Distribution:; Subject: Neuron Digest V11 #13 (discussion) Reply-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu> X-Errors-To: "Neuron-Request" <neuron-request@cattell.psych.upenn.edu> Organization: University of Pennsylvania Date: Tue, 23 Feb 93 10:56:33 EST Message-Id: <4321.730482993@cattell.psych.upenn.edu> Sender: marvit@cattell.psych.upenn.edu Neuron Digest Tuesday, 23 Feb 1993 Volume 11 : Issue 13 Today's Topics: Biologically Plausible Dynamic Artificial Neural Networks Reviewed 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: Biologically Plausible Dynamic Artificial Neural Networks Reviewed From: Paul Fawcett <paulf@manor.demon.co.uk> Date: Sat, 06 Feb 93 18:57:41 +0000 Thank you for publishing in Neuron Digest Vol. 11, Issue 6 my original posting on the subject of 'Biologically Plausible Dynamic Artificial Networks'. As a follow-up to this post I circulated a summary of replies to those who contacted me directly by email. Each contributor agreed to their comments being quoted in this way. Please feel free to use this material, in full or in part, for any future edition of the Neuron Digest. The summary follows: Last update: 20 JAN 93 DISTRIBUTION: Ulf Andrick <andrick@rhrk.uni-kl.de> Mark J. Crosbie <mcrosbie@unix1.tcd.ie> S. E. Fahlman <sef@sef-pmax.slisp.cs.cmu.edu> Bernie French <btf64@cas.org> John R. Mcdonnell <mcdonn%bach.nosc.mil@nosc.mil> Larry D. Pyeatt <pyeatt@texaco.com> Bill Saidel <saidel@clam.rutgers.edu> Mark W. Tilden <mwtilden@math.uwaterloo.ca> Jari Vaario <jari@ai.rcast.u-tokyo.ac.jp> Paul Verschure <verschur@ifi.unizh.ch> Stanley Zietz <szietz@king.mcs.drexel.edu> THIS BULLETIN SUMMARIZES THE MAJORITY OF E-MAIL REPLIES TO THE FOLLOWING USENET ARTICLE: All contributors have agreed to publication of their comments. From: paulf@manor.demon.co.uk (Paul Fawcett) Newsgroups: comp.ai, comp.ai.neural-nets, sci.cognitive, comp.theory.cell-automata, bionet.neuroscience, bionet.molbio.evolution, bionet.software Subject: Biologically Plausible Dynamic Artificial Neural Networks Date: Tue, 05 Jan 93 05:53:57 GMT Biologically Plausible Dynamic Artificial Neural Networks. ------------------------------------------------------------ A *Dynamic Artificial Neural Network* (DANN) [1] [my acronym] possesses processing elements that are created and/or annihilated, either in real time or as some part of a development phase [2]. Of particular interest is the possibility of constructing *biologically plausible* DANN's that models developmental neurobiological strategies for establishing and modifying processing elements and their connections. Work with cellular automata in modeling cell genesis and cell pattern formation could be applicable to the design of DANN topologies. Likewise, biological features that are determined by genetic or evolutionary factors [3] would also have a role to play. Putting all this together with a view to constructing a working DANN, possessing cognitive/behavioral attributes of a biological system is a tall order; the modeling of nervous systems in simple organisms may be the best approach when dealing with a problem of such complexity [4]. Any comments, opinions or references in respect of the above assertions would be most welcome. References. 1. Ross, M. D., et al (1990); Toward Modeling a Dynamic Biological Neural Network, Mathl Comput. Modeling, Vol 13 No.7, pp97-105. 2. Lee, Tsu-Chang,(1991); Structure Level Adaptation for Artificial Neural Networks, Kluwer Academic Publishers. 3. Edleman, Gerald,(1987); Neural Darwinism the Theory of Neural Group Selection, Basic Books. 4. Beer, Randal, D,(1990); Intelligence as Adaptive Behavior : An Experiment in Computational Neuroethology. Academic Press. OVERVIEW The cross-posting strategy was successful in bringing about replies from contributors working in the computer and life sciences. Of those with a computer science background Jari Vaario is constructing (and publishing) DANN's inspired by biological systems and an evolutionary metaphor, John Mcdonnell also reports he has been able to construct evolving networks and Larry Pyeatt has had some success at modeling these processes. Mark Crossbie is interested in combining cellular automata and genetic algorithms to build simple machines. Mark Tilden offers a robotics viewpoint and suggests there may be some 'simple' and 'elegant' solutions. Paul Verschure offers some references to his own work in this field. Life science replies came from Bernie French who suggested the nematode as a suitable organism as model for a DANN. Stanley Zietz has suggested modeling simple structures rather than organisms, and draws attention to the work at NASA-Ames where they are attempting to make 'real' neural networks. To counter this Bill Saidel points out the distinction between the type of neuron being studied in NASA-Ames research and those in the cortex. Thanks to Ulf Andrick and Scott Fahlman for their replies on the Usenet. I hope this discussion will initiate further debate and those who participated will take the opportunity to make some informal contacts with the other contributors. Many thanks Paul. c/o AI Division School of Computer Science University of Westminster 115 New Cavendish Street London W1M 8JS UK. ------------------------------------------------------------- READING The Wolpert and Brown references are suitable for those who do not have a strong background in biology. I would describe Langton's two Artificial Life volumes as essential reading. Artificial Life II contains several papers exploring evolving artificial neural networks. Beer's book is so new I have not been able to look at a copy yet. Title: Biological neural networks in invertebrate neuroethology and robotics / edited by Randall D. Beer, Roy E. Ritzmann, Thomas McKenna. Publication Info: Boston : Academic Press, c1993. Phys. Description: xi, 417 p. : ill. ; 24 cm. Series Name: Neural networks, foundations to applications Subjects: Neural circuitry. Subjects: Invertebrates--Physiology. Subjects: Neural networks (Computer science) ISBN: 0-12-084728-0 Author: Wolpert, L. (Lewis) Title: The triumph of the embryo / Lewis Wolpert ; with illustrations drawn by Debra Skinner. Publication Info: Oxford [England] ; New York : Oxford University Press, 1991. Phys. Description: vii, 211 p. : ill. ; 25 cm. Subjects: Embryology, Human--Popular works. ISBN: 0-19-854243-7 : $22.95 Author: Brown, M. C. (Michael Charles) Title: Essentials of neural development / M.C. Brown, W.G. Hopkins, and R.J. Keynes. Publication Info: Cambridge ; New York : Cambridge University Press, c1991. Phys. Description: x, 176 p. : ill. ; 24 cm. Notes: Rev. ed. of: Development of nerve cells and their connections / by W.G. Hopkins and M.C. Brown. 1984. Subjects: Developmental neurology. Subjects: Nerves. Subjects: Neurons. Subjects: Nerve endings. Subjects: Neurons. ISBN: 0-521-37556-8 ISBN: 0-521-37698-X (pbk.) Title: Artificial life II : the proceedings of an interdisciplinary workshop on the synthesis and simulation of living systems held 1990 in Los Alamos, New Mexico / edited by Christopher G. Langton ... [et al.]. Publication Info: Redwood City, Calif. : Addison-Wesley, 1991. Series Name: Santa Fe Institute studies in the sciences of complexity proceedings ; v. 10 Notes: Proceedings of the Second Artificial Life Workshop. Subjects: Biological systems--Computer simulation--Congresses. Subjects: Biological systems--Simulation methods--Congresses. ISBN: 0-201-52570-4 ISBN: 0-201-52571-2 (pbk.) Author: Interdisciplinary Workshop on the Synthesis and Simulation of Living Systems (1987 : (Los Alamos, N.M.) Title: Artificial life : the proceedings of an Interdisciplinary Workshop on the Synthesis and Simulation of Living Systems, held September, 1987, in Los Alamos, New Mexico / Christopher G. Langton, editor. Publication Info: Redwood City, Calif. : Addison-Wesley Pub. Co., Advanced Book Program, c1989. Phys. Description: xxix, 655 p., [10] p. of plates : ill. (some col.) ; 25 cm. Series Name: Santa Fe Institute studies in the sciences of complexity ; v. 6 ISBN: 0-201-09346-4 ISBN: 0-201-09356-1 (pbk.) ---------------------------------------------------------------------- From: Jari Vaario <jari@ai.rcast.u-tokyo.ac.jp> I have been working already awhile to create a method to describe dynamical neural networks as you describe above. The latest journal papers of mine are Jari Vaario and Setsuo Ohsuga: An Emergent Construction of Adaptive Neural Architectures, Heuristics - The Journal of Knowledge Engineering, vol. 5, No 2, 1992. Abstract: In this paper a modeling method for an emergent construction of neural network architectures is proposed. The structure and behavior of neural networks are an emergent of small construction and behavior rules, that in cooperation with extrinsic signals, define the gradual growth of the neural network structure and its adaptation capability (learning behavior). The inspiration for the work is taken directly from biological systems, even though the simulation itself is not an exact biological simulation. The example used to demonstrate the modeling method is also from biological context: the sea hare Aplysia (a mollusk). Jari Vaario, Koichi Hori and Setsuo Ohsuga: Toward Evolutionary Design of Autonomous Systems, The International Journal in Computer Simulation, A Special Issue on High Autonomous Systems, to be appear 1993. Abstract: An evolutionary method for designing autonomous systems is proposed. The research is a computer exploration on how the global behavior of autonomous systems can emerge from neural circuits. The evolutionary approach is used to increase the repertoire of behaviors. Autonomous systems are viewed as organisms in an environment. Each organism has its own set of production rules, a genetic code, that gives birth to the neural structure. Another set of production rules describe the environmental factors. These production rules together give rise to a neural network embedded in the organism model. The neural network is the only means to direct reproduction. This gives rise to intelligence, organisms which have ``more'' intelligent methods to reproduce will have a relative advantage for survival. Jari Vaario Research Center for Advanced Science and Technology University of Tokyo, Japan JARI HAS OFFERED TO PROVIDE COPIES OF HIS PAPERS TO READERS OF THIS BULLETIN. PLEASE CONTACT HIM BY EMAIL FOR FURTHER DETAILS. --------------------------------------------------------------------- From: "John R. Mcdonnell" <mcdonn%bach.nosc.mil@nosc.mil> I have been developing networks which "evolve" structure as well as the connection strengths. This is done using an evolutionary programming paradigm as a mechanism for stochastic search. One thing I have noticed is that particular structures tend to dominate the population (EP is a multi-agent stochastic search technique). THis has caused me to backtrack a little and investigate the search space for simultaneously determining model structure and parameters. Nevertheless, I have been able to "evolve" networks for simple binary mappings such as XOR, 3-bit parity, and the T-C problem. In the future I am aiming at more general (feedforward) networks which do not have layers per se, but neuron class {input, hidden, output}. Self-organizing of sub-groups of neurons would be an interesting phenomenon to observe for, say, image recognition problems. I think that to accomplish this a distance metric between neurons might be necessary. Fahlman's cascade-correlation architecture is very interesting. However, it has the constraint that the neurons be fully connected to subsequent neurons in the network. This might not be detrimental in that unimportant connections could have very small weights. From an information standpoint, these free parameters should be included in a cost function. I do like his approach in adding additional hidden nodes. As one last comment, when I "evolve" (I use the term loosely) networks for the XOR mapping with an additional input of U(0,1) noise, this third (noisy) input node has all of its outputs disconnected. This was a nice result since inputs which contain no information can be disconnected. John McDonnell NCCOSC, RDT&E Division Code 731 Information & Signal Processing Dept. San Diego, CA 92152-5000 <mcdonn@bach.nosc.mil> ----------------------------------------------------------------------- From: "Larry D. Pyeatt" <pyeatt@texaco.com> I have just completed some code to allow modelling of DANN's. It allows PE's to be created, destroyed, and reconnected at any time........ I have been using genetic algorithms to construct networks with desired properties. Encoding the genes is a major problem....... I have been thinking that it would be interesting to try to evolve or create a simple "creature" which lives in a computer simulated world. The "creature" would have a small set of inputs and responses with which to interact with the simulated world. Once the "creature" has evolved sufficiently, you could make its world richer and give it more neurons. Eventually, you might have a respectably complex organism. Larry D. Pyeatt The views expressed here are not Internet : pyeatt@texaco.com those of my employer or of anyone Voice : (713) 975-4056 that I know of with the possible exception of myself. ----------------------------------------------------------------------- From: Bernie French <btf64@cas.org> I noticed your Usenet post on the use of simple organisms as a model to produce a biologically plausible DANN. One organism that would seem to fit your need for producing a DANN is the nematode, Caenorhabditis elegans. The positions of neuronal processes as well as the neuronal connectivity has been extensively mapped in this organism. The development in terms of cellular fates is also well studied for the nervous system. Integration of neuronal subsystems into the neuronal processes during development have been studied. This would fit your description of a DANN where processing elements are created as part of a development phase. FrologyuLH@Binto atAuronal td) networks which do not have layers per se, but <z controversy and speceyg elementXob0Hld make is we-a1J2hanism-agent mAersy and sTelopmeITAe to allow modelling of DANN's. It allows PE's to be created, destroyed, and reconnected at any time........ I hav-g. However, it has the constraint that the neurons be fully connected to as the5interested|?time......w&wC as th/...w&wC as th/...aNnamnP an InterdThanks >Dtificial N>@sly determining model structure andcontDuRN necessary. 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