| Simulation Home
Introduction
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What is a
computer simulation?
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Despite my earlier claims, this
is, unfortunately, not such an easy question to answer
from the literature. As with many terms
in the literature, computer simulation is not so
much defined as described. Johnson
'defines' a computer simulation as
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...a computer program that defines
the variables of a system, the range of values those
variables may take on, and their
interrelations in enough detail for the system to be set
in motion to generate some output. The
main function of a computer simulations is to
explore the properties and implications
of a system that is too complex for logical or
mathematical analysis... A computer
simulation generally has an ad hoc or “home-made”
quality that makes it less rigorous than
a mathematical model
(1978:186-7)
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Nardi offers as a description:
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A computer simulation model ...
[provides] the investigator with a simplified analogy
... for the purpose of better analysing
and understanding ... [some] phenomenon. ... it
focuses on conducting experiments on a
computer in which mathematical or logical
operations describing the behaviour of a
system over time are of primary importance.
... Its very purpose, in fact, is the
analysis of change over time. ... Computer
simulation is a powerful technique,
capable of handling large numbers of variables
representing complex systems and of
simulating the operation of these variables over
many cycles.
(1980: 38)
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Davies and O'Keefe, in a
programming guide for simulation, suggest:
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When the word [simulation] is used
by computer scientists, statisticians, and
management scientists, they normally
refer to the construction of an abstract model
representing some system in the real
world. The simulation describes the pertinent
aspects of the system as a series of
equations and relationships, normally embedded in
a computer program. (1989:1)
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These descriptions of simulation
might be adequate for many purposes, but it is worth a
closer look at a more structural
definition of simulation in context of how anthropologists
have used them and might use them, if for
no other reason than to provide a basis for
designing simulations and interpreting
the results, a subject treated with extreme coyness
in the literature.
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Specifying the structure of a
simulation is very much like specifying any problem for
computer treatment: we have to visualise
what we want to get out of a simulation, and
devise a structure that will fulfil this
goal. Most descriptions of simulation, especially those
by anthropologists, suggest that a
simulation model is:
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used to model systems
too complex to model with ordinary analytic models
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comprised of logical
or mathematical operations on variables
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able to represent a
large number of variables and operations
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holistic in
orientation, often used to model aspects of entire systems
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oriented towards
representing processes
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oriented towards
exploration and experimentation
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Items an and b
suggest that although simulations are composed of analytic models,
simulations are not necessarily analytic
models (Johnson 1978:186-7). In other words,
simulations can be informal models
defined partly in terms of formal models 18.
Items c
and d reflect a view that
simulations are suitable for modelling complex large scale systems
as well as simple small scale systems
(Johnson 1978:187; Nardi 1980:38), and are thus
'capable of greater realism'
(Johnson 1978:187). Item e expresses a pervasive attitude that
simulations model processes. It is more
accurate to say that simulations produce their
results from one or more processes. These
processes may be used as part of a model of
systemic processes, or they may simply be
artefacts of the simulation 19. Most
simulations
have been used to model processes, but
incorporate both relevant and artefactual
processes. Item f indicates a
pre-analytic bias in the use of simulation; simulations are
oriented towards producing model data for
analysis, not solutions (Buchler et al 1986:
112), although the computer
implementation of a simulation model may include analytic
models which apply to the model generated
data, and simulations may be used in some
cases when no other solution is plausible
or possible (Dyke 1981:204).
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These properties suggest a number
of possible structures, but are not complete. What
distinguishes a simulation model from any
other model forms is not so much the type of
model, but what we do with the model. In
the case of simulations we are interested in the
behaviour of a model; instances of
application of a model. Simulations do not have
solutions in the conventional
sense. The most appropriate purpose of a simulation is to
generate data, representing the
interaction of the models under simulation. The value and
purpose of a simulation follows from what
is done with this model data (Dyke 1981:204).
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Extending this, I propose a more
general structure for computer simulations. Abstractly, a
simulation model consists of at least one
structure, at least one operation which might act
on the structure(s), and at least one
opportunity to apply operation(s) to structure(s)
(Figure 1). It is the applications of one
or more models to create one or more instances. An
operation may or may not be based on an
analytic model; it can be quite ad hoc. A
simulation is at least one instance of an
application of operation to structure. This definition
does not differentiate between the
application of analytic models, such as a discriminant
function derived from social data, and
less formal models, such as those derived from so-
called qualitative analysis of social
data.
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Figure 1. Abstract model of
simulation
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