  Modelling and simulation of complex systems is key to exploring and
understanding social processes, benefiting from formal mechanisms to derive
global-level properties from local-level interactions. In this paper we extend
the body of knowledge on formal methods in complex systems by applying EB-DEVS,
a novel formalism tailored for the modelling, simulation and live
identification of emergent properties. We guide the reader through the
implementation of different classical models for varied social systems to
introduce good modelling practices and showcase the advantages and limitations
of modelling emergence with EB-DEVS, in particular through its live emergence
detection capability. This work provides case study-driven evidence for the
neatness and compactness of the approach to modelling communication structures
that can be explicit or implicit, static or dynamic, with or without multilevel
interactions, and with weak or strong emergent behaviour. Throughout examples
we show that EB-DEVS permits conceptualising the analysed societies by
incorporating emergent behaviour when required, namely by integrating as a
macro-level aggregate the Gini index in the Sugarscape model, Fads and Fashion
in the Dissemination of Culture model, size-biased degree distribution in a
Preferential Attachment model, happiness index in the Segregation model and
quarantines in the SIR epidemic model. In each example we discuss the role of
communication structures in the development of multilevel simulation models,
and illustrate how micro-macro feedback loops enable the modelling of
macro-level properties. Our results stress the relevance of multilevel features
to support a robust approach in the modelling and simulation of complex
systems.
