Scientific models have all these connotations. They are representations of states, objects, and events. They are idealized in the sense that they are less complicated than reality and hence easier to use for research purposes. These models are easier to manipulate and "carry" than the real thing. The simplicity of models, compared with reality, lies in the fact that only the relevant properties of reality are represented.

The word model is used as a noun, adjective, and verb, and in each instance it has a slightly different connotation. As a noun "model" is a representation in the sense in which an architect constructs a small-scale model of a building or a physicist a large-scale model of an atom. As an adjective "model" implies a degree or perfection or idealization, as in reference to a model home, a model student, or a model husband. As a verb "to model" means to demonstrate, to reveal, to show what a thing is like.

The extensive literature addressed to the definition or characterization of science is filled with inconsistent points of view and demonstrates that an adequate definition is not easy to attain. Part of the difficulty arises from the fact that the meaning of science is not fixed, but is dynamic. As science has evolved, so has its meaning. It takes on a new meaning and significance with successive ages.

A great deal of study has been directed to denning 'best decisions,' particularly since the pioneering work of mathematical statisticians (such as Wald), of mathematicians (such as von Neumann), of economists (such as Arrow)... The main effect of this development on the practice of OR has been the growing realization that there are decision objectives other than maximizing expected return and minimizing maximum loss. That is, in many practical situations there are criteria of optimality that are more appropriate than these two mentioned.

The development (rather than the history) of operations research as a science consists of the development of its methods, concepts, and techniques. Operations research is neither a method nor a technique; it is or is becoming a science and as such is defined by a combination of the phenomena it studies.

In the last two decades we have witnessed the emergence of the "system" as a key concept in scientific research. Systems, of course, have been studied for centuries, but something new has been added... The tendency to study systems as an entity rather than as a conglomeration of parts is consistent with the tendency in contemporary science no longer to isolate phenomena in narrowly confined contexts, but rather to open interactions for examination and to examine larger and larger slices of nature. Under the banner of systems research (and its many synonyms) we have also witnessed a convergence of many more specialized contemporary scientific developments... These research pursuits and many others are being interwoven into a cooperative research effort involving an ever-widening spectrum of scientific and engineering disciplines. We are participating in what is probably the most comprehensive effort to attain a synthesis of scientific knowledge yet made.

… All other languages can be translated into the thing-language, but the thing-language cannot be translated into any other language. Its terms can only be reduced to what are called "ostensive" definitions. These consist merely of pointing or otherwise evoking a direct experience. Hence, the thing-language is absolutely basic. Out of this basic language, we build up the other languages of the sciences, beginning with the language of physics, and proceeding to biology, psychology, and the social sciences.