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4 Different Modelling Purposes 53

In a sense, the simulation has illustrated an idea to its creator. One might then exhibit
a version of this simulation to help communicate this idea to others. However, this
does not mean that the simulation achieves any of the other purposes described
above, and it is thus doubtful whether that idea has been established to be of public
value (justifying its communication in a publication) until this happens.
This is not to suggest that illustration is not an important process in science.
Providing new ways of thinking about complex mechanisms or giving us new
examples to consider is a very valuable activity. However, this does not imply its
adequacy for any other purpose.
Definition
An illustration (using a simulation) is to communicate or make clear an idea, theory or
explanation.

Unpacking this:
• Here the simulation does not have to fully express what it is illustrating; it is
sufficient that it gives a simplified example. So it may not do more than partially
capture the idea, theory or explanation that it illustrates, and it cannot be relied
upon for the inference of outcomes from any initial conditions or set-up.
• The clarity of the illustration is of overriding importance here, not its veracity or
completeness.
• An illustration should not make any claims, even of being a description. If it
is going to be claimed that it is useful as a theoretical exposition, explanation or
other purposes, then it should be justified using those criteria—that it seems clear
to the modeller is not enough.

Example In his book, Axelrod (1984) describes a formalised computational ‘game’
where different strategies are pitted against each other, playing the iterated pris-
oner’s dilemma. Some different scenarios are described, where it is shown how the
‘tit for tat’ strategy can survive against many other mixes of strategies (static or
evolving). The conclusions are supported by some simple mathematical consider-
ations, but the model and its consequences were not explored in any widespread
manner. 11 In the book, the purpose of the model is to illustrate the ideas that the
book proposes. The book claims the idea ‘explains’ many observed phenomena, but
in an analogical manner, no precise relationship with any observed measurements is
described. There is no validation of the model here or in the more academic paper
that described these results (Axelrod and Hamilton 1981). In the academic paper,
there are some mathematical arguments which show the plausibility of the model,
but the paper, like the book, progresses by showing the idea is coherent with some
reported phenomena—but it is the ideas rather than the model that are so related.
Thus, in this case, the simulation model is an analogy to support the idea, which
is related to evidence in a qualitative manner—the relationship of the model to
evidence is indirect (Edmonds 2001). Thus, the role of the simulation model is that

11 Indeed, the work spawned a whole industry of papers doing just such an exploration.