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NEXT GENERATION MODELING : A GRAND CHALLENGE
First, I define a few key dimensions of modeling, such as economy, culture and technology, and follow up with how these dimensions will change in the future, and where our research may lead. I conclude the paper with an overview of research we are performing to help move modeling forward by addressing some aspects of these dimensions. Our research aim is to demonstrate key problems in modeling, with partial solutions, along with addressing what is possible for the future to tackle the “grand challenges” of modeling. INTRODUCTION The field of Simulation is usually combined with the term “Modeling” to form “Modeling and Simulation” or perhaps “Simulation Modeling,” Regardless of these terminological differences, modeling plays a key role not only for simulation [1], but for science, engineering and art. To model is to create a structure that captures interesting or noteworthy attributes of a target object. The model of the RMS Queen Mary ship that I have on my shelf is a small metallic piece, and it allows me to experience the ship without setting foot on it. I can become familiar with something that is literally outside of my grasp. By making a target object smaller (as for the Queen Mary) or larger (as for a hexagonal benzene molecule), familiarity with the target is made possible. Modeling dynamical systems has many similarities with these scale models; we need to explore these connections now that technology has permitted us to construct scale models with greater efficiency and economy. Modeling is an amazingly diverse topic whose coverage can be found in just about every discipline. It differs from Analysis or Execution in that the topical area does not command as much attention in the Simulation literature as for Analysis (the mathematical and statistical study of dynamical system behavior) and Execution (the algorithmic analysis of computational efficiency). Modeling does pose major challenges, whose solutions will be felt far outside of the simulation sphere. People speak of models in many ways. A computer program could be seen as a model. Someone may say “I have created a model” but when put to the question of representation, it turns out that they have created a computer program. Then, the question becomes one of representation, which is central to modeling. What representational vehicle did they use, and was program the only representation, or did the model construction begin with other languages and forms and then undergo a sequence of transformations to yield the final program? The area of modeling is all about these forms and the construction process. Modeling is concerned what materials are used to make a structure, how one chooses these materials, and how one interfaces with them. It is a mistake to construe modeling in Computer Simulation to be fundamentally different than modeling found in other areas, such as scale models of the Queen Mary, Eiffel Tower, or a working miniature gas-powered turbine. Also, tasks such as verification and validation are also critical to the overall process of simulation, but they are not the core part of modeling per se; instead, they affect modeling and serve as one of several feedback mechanisms, which help to adjust model structure. One might say that the purpose of modeling is system validation, but apart from the observation that achieving validity is only one aspect of the process of modeling, it is like saying that the purpose of driving is to get to the store. Driving and modeling have their own particular knowledge, ontologies, and processes, bu the means and ends are separate. Modeling, as an interface, lies midway between the human doing the modeling and the thing being modeled. Media become paramount in discussions of model definition, style, aesthetics, and how models are crafted. HISTORY The subject of history might better termed timeline, where we look at the past, the present, and project into the future. For considering grand challenges for modeling, it may behoove us to begin with the future and then return back to the past to collect artifacts relevant to the modeling enterprise. What will history say of our modeling efforts today and in the future? Can we imagine a futuristic modeling environment? One way to imagine the future of modeling is to read books on science fiction and watch modern movies, with their ever-increasing dependence on the latest technologies in computer graphics and post-production techniques that blur the line between “reality” and “simulation.” Disney’s 1982 movie
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