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.
