Path: utzoo!attcan!utgpu!watmath!iuvax!mailrus!uflorida!simulation From: simulation@uflorida.cis.ufl.edu (Moderator: Paul Fishwick) Newsgroups: comp.simulation Subject: SIMULATION DIGEST V10 N7 Message-ID: <20799@uflorida.cis.ufl.EDU> Date: 30 Aug 89 14:01:00 GMT Reply-To: simulation@uflorida.cis.ufl.edu Lines: 309 Approved: fishwick@uflorida.cis.ufl.edu Volume: 10, Issue: 7, Wed Aug 30 10:00:46 EDT 1989 +----------------+ | TODAY'S TOPICS | +----------------+ (1) System Dynamics: A Response (2) Call for Participation: AISIG90 Conference (3) Requesting Papers on Discrete Event Simulation (4) SMPL Report and Questions (5) Call for Papers: AI, Simulation and Planning * Moderator: Paul Fishwick, Univ. of Florida * Send topical mail to: simulation@bikini.cis.ufl.edu OR post to comp.simulation via USENET * Archives available via FTP to bikini.cis.ufl.edu, login as 'anonymous', use your last name as the password, change directory to pub/simdigest. * Simulation Tools available by doing above and changing the directory to pub/simdigest/tools. ----------------------------------------------------------------------------- Date: Thu, 24 Aug 89 06:42 MST From: CELLIER%evax2@rvax.ccit.arizona.edu Subject: RE: System Dynamics (Newsletter) To: Fishwick@bikini.cis.ufl.edu X-Vms-To: IN::"Fishwick@bikini.cis.ufl.edu" One of the more modern (1982) bibliographies of applications of System Dynamics is in my book: "Progress in Modelling and Simulation", Academic Press. The article was written by J.D.Lebel (chapter 8), pp.119-158. I totally agree with you on your remark relating to parameter insensitivity. This statement is a gross simplification. The major problem that I see with System Dynamics lies in the ease of its applicability. It is so easy to create a System Dynamics model with 100 parameters which is impossible to validate on the basis of a usually rather limited set of measurement data. Consequently, you got two problems: (i) System Dynamics does not recognize its own event horizon. I.e., once you created the model, the methodology will be happy to produce trajectory behavior over a ridiculously long time span. Since most systems (e.g. in business) are inherently time-varying, it is YOUR responsibility as a modeler to verify for how long your trajectory behavior may possible be trustworthy. In particular, never use System Dynamics to extrapolate any states far beyond their measured range, e.g., don't use System Dynamics to describe a world model in which the pollution assumes a value which is 100 times larger than any value ever recorded. (ii) A good curve fit between a few measured values and your model is NOT sufficient to validate the structure of your model. Any model can be used to curve-fit any data if it is just made complicated enough (i.e., if enough parameters are added). A System Dynamics model may be valid to predict the future over a limited time horizon, but that does not make it valid to conclude facts from the found model structure. These may be some of the reasons that made System Dynamics somewhat dubious in some people's mind. System Dynamics can still be a great methodology if applied wisely, but DON't succumb to the temptation of falling in love with your System Dynamics model. Blind love usually ends tragic. Your reference to chaotic models is interesting. In fact, most chaotic models are third order or higher Lotka-Volterra type models. The sensitivity comes in at the peak where the first derivative is impressive, and the second derivative is impossible. Interestingly enough, these Lotka-Volterra type models can in fact be looked at as specialized System Dynamics type models (with a small set of parameters). Due to some peculiarities of the error equation, System Dynamics works on THESE models about as well as any other methodology, in spite of the sensitivity problem. One methodology that overcomes some of the deficiencies of System Dynamics is Inductive Reasoning (cf e.g. my paper in Simulation 52:3 (Autopilot)). In this methodology, the model validation process is unseparable from the model building process. Inductive Reasoning will reject to simulate (forecast) the system behavior beyond what can be validated from the available data. It will also give you some insight into the number of parameters that your model can/should contain. Interestingly enough, the larger the number of parameters, the smaller is the event horizon. Once you gained the necessary insight into your model, you can return (if you like) to your System Dynamics methodology, and create models that are validatable on the basis of the available data. Francois Cellier Associate Professor University of Arizona Cellier%ECEVAX@RVAX.CCIT.Arizona.Edu Cellier@Arizevax.Bitnet Looney::Cellier (Span) FCellier (Nasamail) ------------------------------ Date: Thu, 24 Aug 89 10:06:11 -0400 From: Paul Fishwick To: simulation@ufl.edu Subject: AISIG90 Call for Participation CALL FOR PARTICIPATION ---------------------- The Fifth Annual AI SYSTEMS IN GOVERNMENT CONFERENCE ---------------------------------------------------- Date: May 1990 Place: Washington, DC Submission Deadline: Oct. 1, 1989 * Conference Chair * Dr. Barry G. Silverman Institute for AI George Washington University Net: barry@gwusun.gwu.edu * Simulation and Modeling * Point of Contact: Dr. Richard Modjeski Phone: (703)-756-1685 Net: modjeski@alexandria-emh2.army.mil ------------------------------ Posted-Date: Mon, 28 Aug 89 11:56:12 +0200 From: gatech!cs.utexas.edu!uunet.uu.net!prlb2!pirotte@bikini.cis.ufl.edu Date: Mon, 28 Aug 89 11:56:12 +0200 To: bikini.cis.ufl.edu!simulation@cs.utexas.edu Subject: discrete event simulation Cc: uunet.UU.NET!pirotte@cs.utexas.edu I teach a course at the Univ. of Brussels (5th year in engineering curriculum) in which a few lessons are devoted to an introduction to discrete event simulation. To illustrate this part, I give assignments which consist in reading and discussing papers from the technical literature describing simulation experiments. To renew my stock of papers (I do not have an easy access to the specialized literature), I am interested in receiving a copy of technical papers from conferences and journals that describe a particular application (construction of a model, etc.) and the solution with simulation of a problem in the application domain. Paper copies can be sent at the following address: A. Pirotte Philips Research Lab. 2 avenue Van Becelaere 1170 Brussels, Belgium Thank you very much! ------------------------------ Date: Tue, 29 Aug 89 18:15 N From: Patrick Van Renterghem / Transputer Lab Subject: SMPL report/questions To: simulation-maillist@ufl.EDU X-Vms-To: IN%"simulation-maillist@ufl.edu" Comments: From: Patrick Van Renterghem, State University of Ghent References: > The Transputer Lab, Grotesteenweg Noord 2, +32 91 22 57 55 Keywords: > B-9710 Ghent-Zwijnaarde, Belgium, Europe. Fax: +32 91 22 85 91 Dear Simulationists, Several weeks ago, I placed this message on this bulletin board, hoping that someone would provide me with some answers for my questions. But there was not one reply, so I am posting the message again. Please reply to me if you know answers to the questions. Patrick -------------------------------------------------------------------------- This is a short write-up on the porting of the SMPL program (which is available via ftp as described on this mailing list) to our Microvax II/VMS and to a transputer system. * Our C compiler complains about things like '=+' and '=*'. Although this can be easily solved by replacing them by '= +' and '= *', I would recommend to give your equal sign and expressions some more space. Eliminating blanks decreases readibility. * time () and pause () are already in the VAX library. I have replaced the smpl time and pause routines by smpl_time and smpl_pause. * Once these problems were solved, the program ran on the Microvax. We then ported the package to a single transputer system, mainly because we expected it to run a lot faster on a T800 transputer than on a MicroVAX or a PC/AT. And indeed it does. We used 3L's Parallel C and an Inmos B004 board with a T800 and 2 MBytes of slow memory. Naturally, our intention is to get the application running on several transputers. We know all about lockstep and time-warp approaches, but does anyone have an implementation of time-warp that we can use ? * A number of questions remain: - are there any known bugs in smpl ? - is it public domain (can we pass it on ?) ? - would it be possible to have the smpl/PC and mtr () programs as well ? - does anyone have experience with parallelization of discrete event simulation on a distributed memory machine ? ***************************************************************************** * Patrick Van Renterghem, BITNET: pvr@bgerug51.bitnet * * R&D Assistant, EDU: pvr%bgerug51.bitnet@cunyvm.cuny.edu * * State University of Ghent UUCP: mcvax!bgerug51.bitnet!pvr * * Belgium JANET: PVR%earn.bgerug51@earn-relay * * * * Automatic Control Lab/The Transputer Lab, Tel: +32 91 22 57 55 ext. 313 * * State University of Ghent, Fax: +32 91 22 85 91 * * Grotesteenweg Noord 2, * * B-9710 Ghent-Zwijnaarde, Belgium * ***************************************************************************** ------------------------------ Date: Tue, 29 Aug 89 22:55 MST From: ZEIGLER%evax2@rvax.ccit.arizona.edu Subject: call for papers To: fishwick@fish.cis.ufl.edu X-Vms-To: IN::"fishwick@fish.cis.ufl.edu" ANNOUNCEMENT AND CALL FOR PAPERS AI, SIMULATION AND PLANNING IN HIGH AUTONOMY SYSTEMS March 26 - 27, 1990 Sponsoring Agencies: The University of Arizona, College of Engineering and Mines, Department of Electrical and Computer Engineering, Martin Marietta Data Systems and McDonnell Douglas Corporation. In Cooperation With: AT&T, Bell Canada, IEEE Computer Society, Information Machines, NASA-Ames Research Center, Rand Corporation and Siemens Corporate Research. Increasing the autonomy of systems in automation and robotics is a key element in system engineering with such goals as: - reducing the need for human intervention and supervision in remote or hazardous environments. - relieving humans of attending to complex procedures not directly related to their primary objectives. - providing knowledgeable assistance in executing higher level decision making functions. - increasing the rate of decision making beyond that reasonably supportable by a human controller. At the intersection of computers, control, information, and management, design for high autonomy requires the tools of AI and Simulation to successfully integrate decision making and physical layers. Typical issues raised include design stage testability, multi-abstraction model/knowledge bases, discrete/continuous and symbolic/numeric interfaces, self-embedded model construction, and self-planning under behavior constraints. The conference will feature invited and contributed papers in the technical areas of: simulation-evaluated planning and scheduling, qualitative reasoning, device modelling for operations/diagnostics/repair, knowledge-based simulation and design, multi-agent computer architectures and parallel simulators, discrete event dynamic systems, quality assurance issues, intelligent control, model-based perception, model reuse and evolution, embedded learning and adaptation, and related topics. Papers describing applications are also solicited in such areas as autonomous vehicles, telerobotics, factories of the future, design support environments, mission planning support, logistics, wargaming, and in particular, novel applications which fuse modelling paradigms, e.g. combined cognitive/social/natural models and combined neural/symbolic processing. Persons wishing to present papers should submit four copies of an abstract. Abstracts should be not more than three double-spaced pages, including figures and representative citations. Abstracts must be received not later than Friday, November 17, 1989. Mail abstracts to The Office of Engineering Professional Development, University of Arizona, Box 9 Harvill Building, Tucson, AZ 85721, (602) 621-3054 or FAX: (602) 621-1443. Accepted papers will be determined by December 15, 1989. Proceedings will be published in a form permitting wide distribution. Selected papers may be published in a special issue of a major journal. ------------------------------ END OF SIMULATION DIGEST ************************