System Design, Modelling and Simulation, edited by Claudius Ptolemy is HERE. The Preface begins:
My last written work was published nearly 1,900 years ago. I am pleased to come out of retirement to give voice to a project that I’m proud to have named after me, the Ptolemy Project. Like much of my prior work in astronomy and geography, this project deals with complex systems. Like most of my prior writings, this text compiles the thinking and contributions of many people.
The motions of the planets, the sun, the earth, and the moon, which I studied in my work The Almagest, are concurrent interacting processes. They are deterministic, not subject to the whims of the gods. More accurately, the models that I developed, as well as those of many of my successors, deliberately ignore any effects that the gods might capriciously impose. These models focus instead on precisely matching observed behavior, and more importantly, on predicting behavior. The Ptolemy Project similarly studies concurrent processes and focuses on deterministic models.
Ideally, an intellectual quest moves human knowledge from superstition and unfounded beliefs to logic and measurement. What we now call “science,” particularly in the study of natural systems, is deeply rooted in the scientific method, where we form hypotheses, design experiments, and draw conclusions about the hypotheses based on the experiments. To be able to make measurements, of course, the artifact or process being measured must exist in some form. In my earlier studies, this was not an issue, since the sun, earth, moon, and planets already existed. Engineering disciplines, which focus on human-constructed artifacts and processes, however, study systems that do not yet exist. Nevertheless, the scientific method can and is applied in engineering design. Engineers construct simulations and prototypes of systems, formulate hypotheses, and perform experiments to test those hypotheses.
Because of the focus on artifacts and processes that do not yet exist, engineering design should not be based solely on the scientific method. The goal of experiments is to improve our understanding of the artifact or process being designed. But we have to create the artifact or process before we can perform experiments. Being forced to create something before we understand it dooms our design to roots in superstition and unfounded beliefs.
An important part of a science, quite complementary to the scientific method, is the construction of models. Models are abstractions of the physical reality, and the ability of a model to lend insight and predict behavior may form the centerpiece of a hypothesis that is to be validated (or invalidated) by experiment. The construction of models is itself more an engineering discipline than a science. It is not, fundamentally, the study of a system that preexists in nature; it is instead the human-driven construction of an artifact that did not previously exist. A model itself must be engineered.
Good models can even reduce the need for measurement, and therefore reduce the dependence on the scientific method. Once we have a model of the motions of the planets, for example, that we know accurately predicts their positions, there is less need to measure their positions. The role of measurements changes from determining the positions of the planets to improving the models of their motions and to detecting capricious actions of the gods (something that engineers call “fault detection”)...
In short, in engineering, as opposed to science, models play a role in the design of the systems being modelled. As with science, models can be improved, but unlike science, so can the systems being modelled.
