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of the system, which could also be represented with an XM model and this can lead
in easy formalisation, verification (model checking), testing and implementation. The
only condition imposed would be not to test or model check the position (coordinates)
and direction properties, which in turn will result into state explosion.
Simulation of
sp
XMs
4.2
Referring to the initial discussion of this chapter for combining formal with informal
techniques towards the verification of spatial MAS, we suggest that visual animation
can be exploited for detecting the emergent properties of a system. In bio-MAS, an-
imation becomes even more interesting because of the spatial attributes of an agent,
e.g. agents move in an n-dimensional space. An animator as a form of simulation, is
any kind of program which given the code in the intermediate language, implements
an algorithm to facilitate the computation of the model and its output though a tex-
tual description [18, 19]. However, most of the animation techniques share one major
drawback, i.e. the outputs they produce are in a textual form and thus not even close to
the real visual perceptions on the system. Therefore, we focus on a visual simulation
platform, namely NetLogo [18, 20].
NetLogo is a simulation platform for visual animation of multi-agent systems sup-
ported by a functional language that can represent an agent's behaviour, as well as by an
environment for the creation of a graphical user interface. NetLogo facilitates the veri-
fication of a biological model in a way that simulation scenarios may be executed, and
thus the expected behaviour of the system could be compared to the visual outcome.
This platform was our initial choice due to its simplicity and the legacy of work we
have done so far in experimenting with Netlogo features and emergent biological phe-
nomena. Similar but more advanced development toolkits such as Repast [21] should
also be considered as alternatives to visualisation [22].
Given an XM model, it is not always easy nor uniform to map its representation
into the equivalent NetLogo code. This is due to the already discussed disadvantages
in Sec. 3 that deal with the behaviour of the system that represents the motion (and
the other spatial attributes). This raises the question:
Having a model of a system, how
can we visualise it?
sp
XMs overcome the problem found in XMs models, and thus
enhance visual animation, as the agent's position and direction can be interpreted into
motion within an animation platform. This feature opened the horizon towards ideas
for automation of the simulation scenarios for an
sp
XM model, resulting into a tool
sp
XM2Visual.
As it can be noticed from Fig. 4, the
sp
XM2Visual system architecture consists of
two main components, the parser (notifies of possible errors, like type and logical ones)
and the compiler (contains all the rules and the logic for the translation).
Given that NetLogo supports only lists (this is a mathematical structure similar to
the array found in a programming language), in order to produce an equivalent Net-
Logo model from an
sp
XM representation, there was a need of creating an external
library. This external library for NetLogo (included in the compiler of Fig. 4) supports
all the mathematical primitives found in
sp
XMDL (sets, bags, sequences, etc.) and their
operations (see [23] for examples). Moreover, the set of operations from
sp
XMsistrans-
lated within this library as functions (an agent's movement to a certain position, the
