Date: Thu, 30 Apr 1998 11:24:21 -0700 (PDT)
From: John McLeod <mcleod@pauline.sdsc.edu>
To: Takishi Utsumi <utsumi@www.friends-partners.org>
Subject: model integration / modular modeling (fwd)


Tak, I suppose you know about Tom's work, but I want to be sure. Certainly it, or something like it, will be useful for "Peace Gaming", for my concept of global models from national or regional ones, and (in my opinion) a great many other large models.

I have asked Tom to give us an update at our Orlando conference in November (to which I Invited you, but...) and he has accepted. I have also invited Peter Brecke to report on his study of the causes of war, and he has tentatively accepted. You can see that I am trying to give the application of computer modeling and simulation another push toward acceptance by decision-makers worldwide. Can you, will you suggest others whom I should invite?

John

---------- Forwarded message ----------
Date: Wed, 11 Feb 1998 12:18:41 -0500
From: Tom Maxwell <maxwell@CBL.CEES.EDU>
Reply-To: Advanced Technologies in Ecological Science
<ECO-TECH@UMDD.UMD.EDU>
To: ECO-TECH@UMDD.UMD.EDU
Subject: model integration / modular modeling

Web Preprint Available:
"A Meta-Model Approach to Modular Simulation"

http://kabir.cbl.umces.edu/SME3/MetaModelsF.html

Author: Tom Maxwell
University of Maryland Institute for Ecological Economics

We would like to announce the availability of a new preprint describing an approach to model integration and modular modeling. The basic premise of this paper is that the most common approach to model integration, which involves linking procedural models using distributed object formalisms, is greatly limited by the fact that the various sub-models are, by their nature, overspecified as modules. In the process of implementing a sub-model in a procedural programming language, the implementer generally "hard-codes" many choices such as programming language, spatio-temporal representation, model control and IO interfaces, computing paradigm ( serial / parallel-message passing /parallel-shared memory ), etc. When the sub-model enters the collaborative domain as a reusable module these fixed aspects are seen to be extremely limiting and irrelevant to the essential dynamics of the model. In this paper we describe a more flexible approach, which defines archivable modules using abstract model specifications (meta-models) which contain only enough information to specify the essential dynamics of the module and allow a wide range of customized procedural implementations to be generated automatically.

Abstract:

The development of complex models can be greatly facilitated by the utilization of libraries of reusable model components. In this paper we describe an object-oriented module specification formalism (MSF) for implementing archivable modules in support of continuous spatial modeling. This declarative formalism provides the high level of abstraction necessary for maximum generality, provides enough detail to allow a dynamic simulation to be generated automatically, and avoids the hard-coded implementation of space-time dynamics that makes procedural specifications of limited usefulness for specifying archivable modules. A set of these modules can be hierarchically linked within the MSF formalism to create a MSF model.

The MSF exists within the context of a modeling environment ( an integrated set of software tools which provide the computer services necessary for simulation development and execution ), which can offer simulation services that are not possible in a loosely-coupled federated environment, such as graphical module development and configuration, automatic differentiation of model equations, run-time visualization of the data and dynamics of any variable in the simulation, transparent distributed computing within each module, and fully configurable space-time representations. We believe this approach has great potential for bringing the power of modular model development into the collaborative simulation arena.
_________________________________________________________
Thomas P Maxwell, Ph.D. Spatial Systems Research
University of Maryland Institute for Ecological Economics
voice: 410-326-7388 FAX: 410-326-7354
URL: http://kabir.cbl.cees.edu/Tom/Maxwell.html

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