Skip to content

Tom Briggs, PhD

Improve performance. Make work better.

  • BlueSky
  • LinkedIn Profile
  • ResearchGate

About

  • Tom Briggs
  • Use of Affiliate Links

Recent Posts

  • Campbell’s Law: Why your metric will be gamed
  • Why Management Science Fails to Perform, according to Peter Drucker
  • Evicted: Matthew Desmond’s Pulitzer Prize-Winning Ethnography of Tenants, Landlords, and Eviction in an American City
  • Organization Design: “All the elements interact in a system”
  • When is a system complex?

Tags

ABM agent-based modeling bibliometrics book review books boundary spanners career cognition collaboration complexity complexity science computational modeling computational social science conference CSS data data science design of experiments ethics ethnography HR leadership long-tailed distribution management measurement Moore's Law NetLogo network science nonlinearity organizations performance psychology PTCMW quote research methods science scientometrics SNA social network analysis social networks Social Science sociology survey research systems systems thinking

Archives

  • June 2022
  • March 2021
  • August 2019
  • February 2019
  • January 2019
  • November 2018
  • October 2018
  • September 2018
  • July 2018
  • May 2018
  • April 2018
  • January 2018
  • December 2017
  • April 2017
  • March 2017
  • January 2017
  • December 2016
  • November 2016
  • July 2016
  • June 2016
  • March 2016
  • November 2015

Miscellaneous

  • Log in
  • Entries feed
  • Comments feed
  • WordPress.org

Review: An Introduction to Agent-Based Modeling by Uri Wilensky and William Rand

June 10, 2016June 11, 2016 Tom Briggsbook review, complexity science, computational modeling, computational social science

iabm-cover

Uri Wilensky and William Rand’s An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo (find in a library) is the single best book I’ve encountered for anyone interested in agent-based modeling (ABM) in any discipline and at any level (K-12, undergraduate, graduate, professional).

At nearly 500 full-color pages, Wilensky and Rand’s book does an excellent job progressively walking through the decision to use agent-based modeling, creating simple ABMs, extending preexisting ABMs, creating more complicated ABMs, analyzing ABMs, and conducting verification, validation, and replication.

One of the greatest strengths of Wilensky and Rand’s approach is that IABM (Introduction to Agent-Based Modeling) is that it is a hands-on, exploratory book intended for use with the NetLogo multi-agent modeling environment, which is freely available for download. Each chapter of IABM includes many illustrative examples, all implemented and executed in NetLogo. Moreover, the example models and code are not just available to readers (again, free of charge), but are conveniently bundled in the current release of NetLogo. In other words, rather than just read about the models, the reader is encouraged to run the models his or herself. The Chinese proverb says it best:

Tell me and I’ll forget;
show me and I may remember;
involve me and I’ll understand.

Beyond just running the models described in the book, each chapter concludes with a substantial number of exercises or “Explorations,” usually numbering 20 to 30. Each Exploration is a potentially deep opportunity to learn more about ABM by getting involved rather than just reading, as the Chinese proverb suggests.

Wilensky and Rand do a very nice job of using illustrative models from a variety of disciplines; one example might come from the social sciences and the next example from ecology. This is helpful since each reader may come from a different background or have different experience or interests.

The book requires no special background in mathematics or computer science, which is a huge plus in terms of accessibility to a broader audience.

The authors suggest that it could be used as a textbook for an undergraduate course on complex systems or a computer science course on ABM, or even as a supplement to science, social science, or engineering classes. Graduate students who wish to use ABM in their research – regardless of discipline – would likely find IABM one of the best possible places to start. Even experienced researchers with no agent-based modeling experience would benefit from IABM as an introduction to the method.

While the book is aimed at high-level undergraduates and graduate students, it is sufficient to successfully create very detailed and scientifically valuable agent-based models in NetLogo. The authors reserve a final chapter for “advanced” applications potentially of greater interest to individuals interested in specific sorts of ABM: computationally intensive models, participatory or stakeholder-driven modeling, robotics, spatial and geographic information systems (GIS), and network science / social network analysis. They select just a handful of NetLogo’s more advanced capabilities to describe in this chapter, but include helpful references enabling interested readers to learn more.

I can’t find anything about IABM to criticize, though reading it cover to cover (as I did) is certainly an investment of time, albeit a worthwhile one for the reader wishing to learn and use agent-based modeling.

One of the best ways to explore the science of complexity and how complexity theory can be applied to the numerous real-world phenomena we experience and study is through agent-based modeling. Uri Wilensky and Bill Rand have written an excellent book to help anyone do just that, and I recommend An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo (find in a library) to anyone wishing to get started with agent-based modeling.

Wilensky and Rand make ABM accessible and, importantly, thoroughly enjoyable to learn.

The book’s companion website is http://www.intro-to-abm.com/.

Share this:

  • Click to share on X (Opens in new window) X
  • Click to share on LinkedIn (Opens in new window) LinkedIn
  • Click to share on Facebook (Opens in new window) Facebook
  • Click to share on Pocket (Opens in new window) Pocket

Related

Review: An Introduction to Agent-Based Modeling by Uri Wilensky and William Rand

Post navigation

← Data Science, Ethics, and Academics in Industry
Getting Started with Agent-Based Modeling (ABM) →
Proudly powered by WordPress | Theme: Minnow by WordPress.com.
 

Loading Comments...