ABSTRACT
A model is an attempt to capture the essence of things. Hence, as a rule, a model strives to be as simple as possible, admitting complexity only as necessary. This is a very sensible rule, in fact. Approaches that disregard it tend to produce a muddle rather than a model—an insight I owe to Valentino Braitenberg. Thus, we generally use models as simplified versions of reality. They summarize our knowledge from previous experiments, allow us to make predictions to be tested in new experiments, and, above all, they enable us to make a conceptual interpretation of our results and insights.
