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3 Types of Simulation 31

i.e. the topology does not change during a simulation, or dynamic. In these networks,
interaction is typically language-based. An example is the work by Verhagen
(2001), where agents that are part of a group use direct communication between
the group members to form shared group preferences regarding the decisions they
make. Communication is steered by the structure of the social network regardless of
the physical location of the agents within the simulated world. For a more detailed
discussion of the different options to model interaction topologies, see Chap. 19 in
this volume (Amblard and Quattrociocchi 2017).

3.4.3 The Environment

The state of the environment is usually represented by a set of (global) parameters,
e.g. temperature. In addition, there are a number of important aspects of the
environment model, such as:
– Spatial explicitness: In some models, there is actually no notion of physical
space at all. An example of a scenario where location is of less importance
are “innovation networks” (Gilbert et al. 2001). Individual agents are high-
tech firms that each have a knowledge base used to develop artefacts to launch
on a simulated market. The firms are able to improve their products through
research or by exchanging knowledge with other firms. However, in many
scenarios, location is very important; thus, each individual (and sometimes
objects) is assigned a specific location at each time step of the simulation. In
this case, the individuals may be either static (the entity does not change location
during the simulation) or mobile. The location could either be specified as an
absolute position in the environment or in terms of relative positions between
entities. In some areas, the simulation software is integrated with a Geographical
Information System (GIS) in order to achieve closer match to reality (cf. Schüle
et al. 2004).
– Time: There are in principle two ways to address time, and one is to ignore it. In
static simulation, time is not explicitly modelled; there is only a “before” and an
“after” state. However, most simulations are dynamic, where time is modelled as
a sequence of time steps. Typically, each individual may change state between
each time step.
– Exogenous events: This is the case when the state of the environment, e.g.
the temperature, changes without any influence/action from the individuals.
Exogenous events, if they are modelled, may also change the state of entities,
e.g. decay of resources, or cause new entities to appear. This is a way to make
the environment stochastic rather than deterministic.