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7 Checking Simulations: Detecting and Avoiding Errors and Artefacts 137

framework we have identified the different types of errors and artefacts that may
occur in each of the stages of the modelling process. Finally, we have proposed
several activities that can be conducted to avoid each type of error or artefact.
Some of these activities include repetition of experiments in different platforms,
reimplementation of the code in different programming languages, reformulation
of the conceptual model using different modelling paradigms, and mathematical
analyses of simplified versions or particular cases of the model. Conducting these
activities will surely increase our understanding of a particular simulation model.

Acknowledgements The authors have benefited from the financial support of the Spanish
Ministry of Education and Science (projects CSD2010-00034, DPI2004-06590, DPI2005-05676,
and TIN2008-06464-C03-02) and of the Junta de Castilla y León (projects BU034A08 and
VA006B09). We are also very grateful to Nick Gotts, Gary Polhill, Bruce Edmonds, and Cesáreo
Hernández for many discussions on the philosophy of modelling.

Further Reading

Gilbert (2007) provides an excellent basic introduction to agent-based modelling.
Chapter 4 summarises the different stages involved in an agent-based modelling
project, including verification and validation. The paper entitled “Some myths and
common errors in simulation experiments” (Schmeiser 2001) discusses briefly some
of the most common errors found in simulation from a probabilistic and statistical
perspective. The approach is not focused specifically on agent-based modelling but
on simulation in general. Yilmaz (2006) presents an analysis of the life cycle of a
simulation study and proposes a process-centric perspective for the validation and
verification of agent-based computational organisation models. An antecedent of
this chapter can be found in Galán et al. (2009). Finally, Chap. 9 in this volume
(David et al. 2017) discusses validation in detail.

References

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Axtell, R. L. (2000). Why agents? On the varied motivations for agent computing in the
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