Simulating Social Complexity: A Handbook
Bruce Edmonds, Scott Moss, Ruth Meyer - Springer, 2012
Social systems are among the most complex
known. This poses particular problems for those who wish to understand them. The
complexity often makes analytic approaches infeasible and natural language
approaches inadequate for relating intricate cause and effect. However,
individual- and agent-based computational approaches hold out the possibility of
new and deeper understanding of such systems. Simulating Social Complexity
examines all aspects of using agent- or individual-based simulation. This
approach represents systems as individual elements having each their own set of
differing states and internal processes. The interactions between elements in
the simulation represent interactions in the target systems. What makes these
elements "social" is that they are usefully interpretable as interacting
elements of an observed society. In this, the focus is on human society, but can
be extended to include social animals or artificial agents where such work
enhances our understanding of human society. The phenomena of interest then
result (emerge) from the dynamics of the interaction of social actors in an
essential way and are usually not easily simplifiable by, for example,
considering only representative actors. The introduction of accessible
agent-based modelling allows the representation of social complexity in a more
natural and direct manner than previous techniques. In particular, it is no
longer necessary to distort a model with the introduction of overly strong
assumptions simply in order to obtain analytic tractability. This makes
agent-based modelling relatively accessible to a range of scientists. The
outcomes of such models can be displayed and animated in ways that also make
them more interpretable by experts and stakeholders. This handbook is intended
to help in the process of maturation of this new field. It brings together,
through the collaborative effort of many leading researchers, summaries of the
best thinking and practice in this area and constitutes a reference point for
standards against which future methodological advances are judged. This book
will help those entering into the field to avoid "reinventing the wheel" each
time, but it will also help those already in the field by providing accessible
overviews of current thought. The material is divided into four sections:
Introductory, Methodology, Mechanisms, and Applications. Each chapter starts
with a very brief section called 'Why read this chapter?' followed by an
abstract, which summarizes the content of the chapter. Each chapter also ends
with a section of 'Further Reading' briefly describing three to eight items that
a newcomer might read next.
