Handbook: Simulating Social Complexity

A handbook on Simulating Social Complexity
edited by Bruce Edmonds and Ruth Meyer
in memory of Herbert Simon

Publisher’s page

Advisors (in alphabetical order):

  • Alexis Drougol
  • Blake LeBaron
  • Francous Bousquet
  • Guillaume Deffuant
  • Jim Doran
  • Klaus Troitszch
  • Kuni Kaneko
  • Michael Macy
  • Nigel Gilbert
  • Paul Thagard
  • Robert Axtell
  • Rosaria Conte
  • Wander Jager


To be an authoritative snap-shot of the science of simulating social complexity, that will be used as a reference point for researchers during the following 10 years. To facilitate the introduction of researchers into the field and generally to promote its achievements.

Simulating – the focus is on individual- or agent-based computational simulation rather than approaches that focus on analytic or natural language approaches (although these can be involved).

Social – the elements under study have to be usefully interpretable as interacting elements of a society. The focus will be on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society.

Complexity – the phenomena of interest are those that result from the interaction of social actors in an essential way and not those that are reducible to considering single actors or a representative actor and a representative environment. It is this complexity that (typically) makes analytic approaches infeasible and natural language approaches inadequate for relating cause and effect. This complexity is expressed in many different ways, for example: as a macro/micro link; as the social embedding of actors within their society; as emergence; etc.

This scope means that most economics (even evolutionary or agentified economics) or physics is outside the scope of this handbook (these would take handbook of their own), but will often be mentioned as it relates to the material in this book.

The book is intended to be more of an encapsulation of the best state-of-the-art, rather than a recapitulation of the development of the field (though there will be a chapter on the history and many chapters will, no doubt refer to the history). Thus although this area has resulted from researchers converging on this area from diverse fields (sociology, anthropology, economics, physics, computer science, artificial life etc.) this book will emphasise what unity and consensus exists (whilst acknowledging and pointing out important issues of contention) rather than the different perspectives and fields that academics may view it from.

Outline of Book

1.Introductory Section
1.1. Introduction to the handbook
1.2. Historical Introduction

2. Methodology and Tools

Purpose of section: to provide a “how to guide” representing the best present practice, including: a summary of the main approaches currently used, indications of how to go about putting them into practice, the pros/cons of approaches and dangers/difficulties, sources and literature for further investigation/study.

2.1. Types of Simulation
2.2. Building Simulations
2.3. Understanding Simulations
2.4. Manipulating Simulations
2.5. Validating Simulations
2.6. Understanding Simulation Results
2.7. Participatory Approaches
2.8. Combining Analytic and Simulation Approaches
2.9. Interpreting and Understanding Simulations

3. Mechanisms and Structures

Purpose of section: to provide a summary of the different kinds of mechanism; their implementation and known effects so that a reader has a feel for what works, what has been explored, and where to start. This list inevitably misses out many mechanisms that are, no doubt, important but which have not (yet) been substantially explored in simulation work, e.g. semantic communication.

3.1. Utility, games and haggling
3.2. Social Constraint
3.3. Trust and Reputation
3.4. Groups
3.5. Power and Authority
3.6. Spatial distribution
3.7. Evolution and Learning

4. Application Areas

Purpose of section: Outlines areas where this work is being applied or is close to being applied. Not to include areas where there are no credible results/models or where social aspects do not play a prominent part. Obviously to concentrate on those areas where complex simulations have played a significant part rather than those cases where traditional approaches have done well.

4.1. Ecological management
4.2. Assessing organisational design
4.3. Distributed computer systems
4.4. Animal social behaviour
4.5. Markets
4.6. Movement of people and goods
4.7. Understanding Human Societies

5. End Matter
5.1. Reflective Epilogue
5.2. Combined Bibliography
5.3. List of Resources