Agent-Based Computational Sociology

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Product Description

Most of the intriguing social phenomena of our time, such as international terrorism, social inequality, and urban ethnic segregation, are consequences of complex forms of agent interaction that are difficult to observe methodically and experimentally. This book looks at a new research stream that makes use of advanced computer simulation modelling techniques to spotlight agent interaction that allows us to explain the emergence of social patterns. It presents a method to pursue analytical sociology investigations that look at relevant social mechanisms in various empirical situations, such as markets, urban cities, and organisations. 

This book:

• Provides a comprehensive introduction to epistemological, theoretical and methodological features of agent-based modelling in sociology through various discussions and examples.
• Presents the pros and cons of using agent-based models in sociology.
• Explores agent-based models in combining quantitative and qualitative aspects, and micro- and macro levels of analysis.
• Looks at how to pose an agent-based research question, identifying the model building blocks, and how to validate simulation results.
• Features examples of agent-based models that look at crucial sociology issues.
• Supported by an accompanying website featuring data sets and code for the models included in the book.

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Agent-Based Computational Sociology is written in a common sociological language and features examples of models that look at all the traditional explanatory challenges of sociology. Researchers and graduate students involved in the field of agent-based modelling and computer simulation in areas such as social sciences, cognitive sciences and computer sciences will benefit from this book.

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Agent-Based Computational Sociology Review

The primary purpose of this book is not to teach you how to program an agent-based model, although it contains the code for two agent-based models in Appendix B.

What this book will do is teach you how to bring sociological theory into building your agent-based models. Because this book is an introduction to agent-based modelling, this is the first book I have read on the subject, to get a general grounding. The literature cited is extensive, with a focus on sociology-related books and articles. Some economics-based agent-based modelling literature is also used.

Chapter 1: introduces agent-based modelling and uses six themes to describe the modelling. While I disagree with some of his points, for example discrete event simulation can also be characterised as having "trans-disciplinarity", these themes are useful in identifying the important advantages of agent-based modelling. There is also a section on the characteristics of different types of models and while I don't think that the types are as different as portrayed (e.g. there may be little differences between case-based models and applied simulation in practice), this is useful in showing the different types of questions that agent-based models can help to answer.

Chapter 2: this introduces and describes various agent-based models that address cooperation, coordination, and social norms. The importance of each model is mentioned, and its place in the historical context of these sociological principles is identified. Some of the results of the simulations are reproduced, to illustrate points. This is a good overview of the importance of considering how agents can be programmed to affect each other, with solid examples.

Chapter 3: agent-based models are spatial models, so the interactions of the agent personalities cause agents to re-situate themselves in space. Schelling's segregation models (and later variants by other modellers) are used to illustrate the start of this chapter, followed by sections on threshold/tipping point which contains a number of papers looking at extremism propagation, and their extensions as highlighted by the work of Axelrod and the author.

Chapter 4: while this chapter is titled "Methodology", it is actually concerned with the verification and validation of agent-based models. Does the model represent reality in the way it is intended? Is it programmed correctly? Are the results of the simulation replicable? Are the outputs of the simulation useful? This is an excellent introduction to these processes, with an extensive outline of articles that demonstrate the importance of performing both verification and validation.

If you are new to agent-based modelling and/or a social scientist interested in shifting into working in this area, this book is an excellent grounding in the sociological ideas underpinning the simulations.

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