Choosing the right model

Abstract

Models are representations of artefacts or situations that are developed for a prescribed purpose. The authors consider models to be executable descriptions of the real world; that is a model can be used to predict or analyse properties of the system. Simulation and reasoning systems, which may be derived from traditional or AI approaches, are used to execute these models. Given the plethora of modelling techniques available which cope well with certain, but not other, contexts, it is evident that there is no ‘best model’ covering all situations: a model is correct if it satisfies its purpose no less and no more. The desires of the user of a modelling system are always moderated by the availability of techniques permitting these desires to be met. To alleviate the difficulties associated with this requires a methodology to guide the user to the best model and simulation technique to meet his needs. A primary requirement in the construction of such a methodology is a comprehensive and understandable classification of the choices inherent in the construction of a model.