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also helped us to develop simulation models that are easy to maintain and easy to
extend. Rather than building a model from scratch every time we start a new study,
we can reuse previously developed model components with confidence. Using a
formal approach to modelling is also a big benefit when it comes to publications as
the resulting models are transparent and well documented.

Further Reading

There is a host of literature on the topic of software engineering. A book that
provides a comprehensive yet easy to understand entry to most of the software
engineering topics discussed in this book chapter is Lethbridge and Laganiere
(2005). If you are mainly interested in learning more about UML, then Fowler
(2003) is sufficient. A lot of ideas for ABSS stem from the computer science field
of artificial intelligence and herein particular multi-agent systems. A good overview
on the wide area of topics (including AOSE) is Weiss (2013). Finally, the JASSS
special issue “Engineering ABSS” (Siebers and Davidsson 2015) provides lots of
information and case studies. The approach contrasts with that described in Chap. 5
in this volume.

References

Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An
integrated theory of the mind. Psychological Review, 111(4), 1036–1060.
Bauer, B., & Odell, J. (2005). UML 2.0 and agents: How to build agent-based systems with the new
UML standard. Journal of Engineering Applications of Artificial Intelligence, 18(2), 141–157.
Beck, K. (2004). Extreme programming explained: Embrace change (2nd ed.). Boston, MA:
Addison Wesley.
Bedwell, B., Leygue, C., Goulden, M., McAuley, D., Colley, J., Ferguson, E., et al. (2014).
Apportioning energy consumption in the workplace: A review of issues in using metering data
to motivate staff to save energy. Technology Analysis & Strategic Management, 26(10), 1196–
1211.
Bergenti, F., Gleizes, M.-P., & Zambonelli, F. (Eds.). (2004). Methodologies and software
engineering for agent systems: The agent-oriented software engineering handbook. Boston:
Kluwer.
Bersini, H. (2012). UML for ABM. Journal of Artificial Societies and Social Simulation, 15(1), 9.
http://jasss.soc.surrey.ac.uk/15/1/9.html
Boero, R., & Squazzoni, F. (2005). Does empirical embeddedness matter? Methodological issues
on agent-based models for analytical social science. Journal of Artificial Societies and Social
Simulation, 8(4), 6. http://jasss.soc.surrey.ac.uk/8/4/6.html
Bosse, T., Jonker, C. M., van der Meij, L., & Treur, J. (2005). LEADSTO: A language and
environment for analysis of dynamics by simulation. In T. Eymann, F. Klügl, W. Lamersdorf,
M. Klusch, & M. N. Huhns (Eds.), Proc. of the 3rd German Conference on Multi-Agent System
Technologies, MATES’05. LNAI 3550 (pp. 165–178). Springer, Berlin, Heidelberg, Germany.
Bommel, P., & Müller, J. P. (2007). An introduction to UML for modelling in the human and social
sciences. In D. Phan & F. Amblard (Eds.), Multi-agent modelling and simulation in the social