Dissecting the words in his description, “a physical system” can be broadly interpreted
as any real-world problem—natural or man-made, discrete or continuous and
can be deterministic, chaotic, or random in behaviour. The context of the system
could be physical, chemical, biological, social, economic or any other setting that
provides observed data or phenomena that we would like to quantify. Being “adequate”
sometimes suggests having a minimal level of quality, but in the context of
modelling it describes equations that are good enough to provide suf?ciently
accurate predictions of the properties of interest in the system without being too
dif?cult to evaluate.
Trying to include every possible real-world effect could make for a complete
description but one whose mathematical form would likely be intractable to solve.
Likewise, over-simpli?ed systems may become mathematically trivial and will not
provide accurate descriptions of the original problem. In this spirit, Albert Einstein
supposedly said, “Everything should be made as simple as possible, but not simpler”
[107], though ironically this is actually an approximation of his precise
statement [34].
Many scientists have expressed views about the importance of modelling and the