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An abstract model (or conceptual model) is a theoretical construct that represents Physical , Biological or Social processes, with a set of variables and a set of logical and quantitative relationships between them. Models in this sense are constructed to enable Reasoning within an idealized logical framework about these processes and are an important component of Scientific Theories . ''Idealized'' here means that the model may make explicit assumptions that are known to be false in some detail. Such assumptions may be justified on the grounds that they simplify the model while, at the same time, allowing the production of acceptably accurate solutions, as is illustrated below. EXAMPLES Mathematical models ''Main article:'' Mathematical Model
:: :Note this model assumes that the particle is a point mass, which is certainly known to be false in many cases where we use the model, e.g. when we use it as a model of planetary motion.
:: :subject to :: : This model has been used in models of general equilibrium theory, particularly to show existence and Pareto Optimality of economic equilibria. However, the fact that this particular formulation assigns ''numerical values'' to levels of satisfaction is a source of criticism. But this is not an essential ingredient of the theory and again, the model ''is'' an idealization. Other types of models These two models are examples of mathematical models; following are examples of models that are not mathematical (or at least not numerical).
USE OF MODELS The purpose of a model is to provide an '' Argumentative Framework '' for applying logic and mathematics that can be independently evaluated (for example by testing) and that can be applied for reasoning in a range of situations. Models are used throughout the natural and social sciences, psychology and the philosophy of science. Some models are predominantly Statistical (for example portfolio models used in finance); others use calculus, linear algebra or convexity, see Mathematical Model . Of particular political significance are Models used in economics, since they are used to justify decisions regarding taxation and government spending. This often leads to hotly contested debates in the Academic world as well as in the political arena; see for instance Supply Side Economics . Abstract models are used primarily as a reusable tool for discovering new facts, for providing systematic Logical Argument s as explicatory or pedagogical aids, for evaluating hypotheses theoretically, and for devising experimental procedures to test them. Reasoning within models is determined by a set of logical principles, although rarely is the reasoning used completely mathematical. In some cases, abstract models can be used to implement Computer Simulation s that illustrate the behavior of a system over time. Simulations are used everywhere in science, especially in Economics , Engineering , Biology , Ecology etc., to discover the effects of changing a variable. The validity of different simulation methodologies is a subject of debate in the philosophy and methodology of science. STRUCTURE OF MODELS :''Main article: Conceptual Schema A conceptual model is a representation of some phenomenon by logical and mathematical objects such as Function s, Relation s, tables, Stochastic Process es, formulas, axiom systems, rules of inference etc. A conceptual model has an Ontology , that is the set of expressions in the model which are ''intended'' to denote some aspect of the modeled object. Here we are deliberately vague as to how expressions are constructed in a model and particularly what the logical structure of formulas in a model actually is. In fact, we have made no assumption that models are encoded in any Formal Logical system at all, although we briefly address this issue below. Moreover, the definition given here is oblivious about whether two expressions really should denote the same thing. Note that this notion of ontology is different from (and weaker than) ontology as is sometimes understood in philosophy; in our sense there is no claim that the expressions actually denote anything which exists ''physically'' or ''spatio-temporally'' (to use W. Quine's formulation). For example, a stochastic model of stock prices includes in its ontology a sample space, random variables, the mean and variance of stock prices, various regression coefficients etc. Models of Quantum Mechanics in which Pure State s are represented as unit vectors in a Hilbert space include in their ontologies Observable s, Dynamics , Measurement operators etc. It is possible that observables and states of quantum mechanics are as physically real as the electrons they model, but by adopting this purely formal notion of ontology we avoid altogether this question. MODELING Modeling , especially Scientific Modeling refers to the process of generating a model as a conceptual representation of some phenomenon as discussed above. Typically a model will refer only to some aspects of the phenomenon in question, and two models of the same phenomenon may be essentially different, that is in which the difference is more than just a simple renaming. This may be due to differing requirements of the model's end users or to conceptual or esthetic differences by the modellers and decisions made during the modeling process. Esthetic considerations that may influence the structure of a model might be the modeller's preference for a reduced Ontology , preferences regarding Probabilistic Model s vis-a-vis deterministic ones, discrete vs continuous time etc. For this reason users of a model need to understand the model's original purpose and the assumptions of its validity. Having found a model for some desired aspect of reality, it can serve as the basis for Simulation , the only way for non-invasive examination of physical reality besides real-world Experiment s. REFERENCES
SEE ALSO
Modeling languages
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