Prototype ABM of consumer behaviour

Last summer I worked with my colleague Dr Andy Newing and a Master’s dissertation student, Charlotte Sturley, who has just won the Royal Geographical Society GIS group prize for best dissertation.  Her work focused on classifying consumer data into several groups of behaviour and then building a prototype ABM using NetLogo.

This work posed several challenges: how do we translated observed behaviour into rules that an agent can operate satisfactorily? How should we represent time to mimic temporal as well as spatial patterns in different types of consumer behaviour?  Which of the many processes involved within this system should we include?  Charlotte’s dissertation (and upcoming paper) addresses these issues in-depth, but in brief the data was analysed in depth (using classification methods and spatial analysis tools) to identify different groups of individuals and their behaviour.  We built a highly abstract representation of Leeds which allowed us to match behaviour to the corresponding geodemographic classifications and add in real store distributions.   These can be seen below with the red blobs representing different types of stores and the coloured squares representing different areas of Leeds and the different consumer types that reside there.


This is, of course, a highly abstract representation of what is a very complex system and clearly a significant amount of development to the model would be required to fully replicate the real system.  However, one of the research questions that we were interested in addressing was whether  ABM could replicate the pull of consumers to a store based on distance and attractiveness i.e. could we embed this aspect of a spatial interaction model into an ABM?  The answer was yes, and this represents a potentially important shift in the methods by which retailers simulate the likely consequences of different policies on consumer behaviour.

More details on this work can be found in Charlotte’s upcoming paper.  A copy of the model code can be downloaded here.

ABM Congress, Washington

abmcongressI attended the International Congress on Agent Computing at George Mason University (US) last month.  It was organised to mark the 20th anniversary of the publication of Robert Axtell and Joshua Epstein‘s landmark work,  Growing Artificial Societies and as such was both a celebration and a reflection on how far the discipline has progressed over the last 20 years.

While it is clear that in some areas there has been great gains, such as the size and complexity of ABMs (not to mention the sheer number of applications – Robert Axtell in his presentation gave the following figures based on a keyword search of publications: 1K papers per year on IBM; 10K per year on MAS and 5K per year on ABM), I see these gains as mainly attributable to advances in software and availability of data and not because we are tackling the big methodological problems.  I would strongly agree with Axtell that ABMs are still ‘laboratory animals’ and not yet ready for uptake in policy.  This view surprisingly contrasted with Epstein who in his opening remarks described ABM as a ‘mature scientific instrument’, perhaps nodding towards the large numbers of (often bad) ABMs that are continually appearing.  However, Epstein did agree with Axtell in the discussion of several challenges/definitive work that ABM needs to take on such as creating cognitively plausible agents (accompanied by a big plug for Epstein’s recent book, Agent Zero, on this very topic), not getting side stepped by big data:  “Data should be as big as necessary, but no bigger” (a nice play on the Einstein ‘models should be as simple as possible, but no simpler’) and calibrating to large scale ABMs.

It is this last point, that of calibration and validation that can be blamed for my grumpy mood throughout most of the Congress presentations.  There was some fantastic work, creating very complex agents and environments, but these models were calibrated and validated using simple statistics such as R^2!  Complex models = (often) complex results, which in turn requires complex analysis tools.  By the time that my presentation time came around on the last afternoon, I was in the mood for a bit of a rant…which is exactly what I did! But I’d like to think I did it in a professional way…  I presented a joint talk with Andrew Crooks and Nick Malleson entitled “ABM for Simulating Spatial Systems: How are we doing?” which reflected on how well (or not) ABM of geographical systems has advanced over the last 20 years.



We argued that while as geographers we are very good at handling space (due to GIS), we’re not very good at representing the relationships and interactions (human to human and human to environment).  We also need to look closely at how to scale up individual agents; for example how can we take an agent created at the neighbourhood level, with its own rules and explicit use of space and scale this up to the city level (preserving all the characteristics and behaviours of that agent)?  Work needs to be done now to shape how we use Big Data to ensure that it becomes an asset to ABM, not a burden.  And then I moved on to calibration and validation!  It wasn’t all gloom, the presentation featured lots of eye candy thanks to Nick and Andrew.

While the congress brought together an interesting line up of interdisciplinary keynote speakers: Brian ArthurMike BattyStuart Kauffman and  David Krakauer  – all were men.  Of the 19 posters and 59 presentations,  only a handful were women.  I find this lack of diversity disappointing (I refer here to gender, but this could equally be applied to other aspects of diversity).  While women are in the minority in this discipline, we do have a presence and such an event reflecting on the past, and celebrating a promising future should have fully reflected this.

However, I don’t wish to end on a negative note, the Congress was fantastic in the breadth of work that it showcased, and because it was so small, it had a genuinely friendly and engaging feel to it.  The last word should go to Epstein who I felt summarised up ABM nicely with the following: “As a young science, [it has made] tremendous progress and [has great] momentum”.


Heppenstall, A., Crooks A.T. and Malleson, N. (2016)ABM for Simulating Spatial Systems: How are we doing? International Congress on Agent Computing, 29th-30th, November, Fairfax, VA.

Geocomputation 2017: Workshop Invitation


In preparation for GeoComputation 2017, we’re now open for volunteers who would like to put on workshops. We welcome applications and suggestions in any GeoComputational area, new and more established. The main day for workshops will be the 3rd Sept 2017, just before the conference.

However, we would also like to run some little mini-hackathon things during some of the breaks/lunches, so if anyone has any ideas for short and sweet little interactive training bursts, or other activities that engage people in exciting technologies, please get in touch. All ideas welcome. Email Andy Evans on, or

Conference website here.


Call for Papers – Symposium on Human Dynamics in Smart and Connected Communities: Agents – the ‘atomic unit’ of social systems?

Call for Papers – Symposium on Human Dynamics in Smart and Connected Communities: Agents – the ‘atomic unit’ of social systems?

We welcome paper submissions for our session(s) at the Association of American Geographers Annual Meeting on 5-9 April, 2017, in Boston.

Session Description:

By defining a social system as a collection of agents, individuals and their behaviors/decisions become the driving force of these systems. Complex global phenomena such as collective behaviors, extensive spatial patterns, and hierarchies are manifested through agent interaction in such a way that the actions of the parts do not simply sum to the activity of the whole. This allows unique perspectives into the inner workings of social systems, making agent-based modelling (ABM) a powerful and appealing tool for understanding the drivers of these systems and how they may change in the future.

What is noticeable from recent applications of ABM is the increase in complexity (richness and detail) of the agents, a factor made possible through new data sources and increased computational power. While there has always been ‘resistance’ to the notion that social scientists should search for some ‘atomic element or unit’ of representation that characterizes the geography of a place, the shift from aggregate to individual mark agents as a clear contender to fulfill the role of ‘atom’ in social simulation modelling. However, there are a number of methodological challenges that need to be addressed if ABM is to fully realize its potential and be recognized as a powerful tool for policy modelling in key societal issues. Most pressing are methods to accurately identify, represent, and evaluate key behaviors and their drivers in ABM.

We invite any papers that contribute towards this wide discussion ranging from epistemological perspectives of the place of ABM, extracting behavior from novel and established data sets to new, intriguing applications to establishing robustness in calibrating and validating ABMs.

Please e-mail the abstract and key words with your expression of intent to Andrew Crooks ( by 22nd October, 2016 (one week before the AAG session deadline). Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at:

An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.

Timeline summary:

  • 20th October, 2016: Abstract submission deadline. E-mail Andrew Crooks by this date if you are interested in being in this session. Please submit an abstract and key words with your expression of intent.
  • 24th October, 2016: Session finalization and author notification
  • 26th October, 2016: Final abstract submission to AAG, via All participants must register individually via this site. Upon registration you will be given a participant number (PIN). Send the PIN and a copy of your final abstract to Andrew Crooks. Neither the organizers nor the AAG will edit the abstracts.
  • 27th October, 2016: AAG registration deadline. Sessions submitted to AAG for approval.
  • 5-9th April, 2017: AAG Annual Meeting.


  • Andrew Crooks, Department of Computational and Data Sciences, George Mason University.
  • Alison Heppenstall, School of Geography, University of Leeds.
  • Nick Malleson, School of Geography, University of Leeds
  • Paul Torrens, Department of Computer Science and Engineering, Tandon School of Engineering, New York University.
  • Sarah Wise, Centre for Advanced Spatial Analysis (CASA), University College London.

Agent-based Modelling in Geographical Systems

Recently Andrew Crooks and I wrote a short introductory chapter entitled “Agent-based Modeling in Geographical Systems” for AccessScience (a online version of McGraw-Hill Encyclopedia of Science and Technology).

In the chapter we trace the rise in agent-based modeling within geographical systems with a specific emphasis of cities. We briefly outline how thinking and modeling cities has changed and how agent-based models align with this thinking along with giving a selection of example applications. We discuss the current limitations of agent-based models and ways of overcoming them and how such models can and have been used to support real world decision-making.
Conceptualization of an agent-based model where people are connected to each other and take actions when a specific condition is met

 Full Reference:

Heppenstall, A. and Crooks, A.T. (2016). Agent-based Modeling in Geographical Systems, AccessScience, McGraw-Hill Education, Columbus, OH. DOI: (pdf)

Charge of the Lycra Brigade…

20160422_083513Its inevitable that I would be drawn into doing some work about cycling – I live in a small market town that is overrun by crazy people donning lycra and heading to the hills.  The Tour de Yorkshire is the latest in a series of major cycle events that is coming through my town this weekend.  We were lucky enough to be on the route of Le Grand Depart back in July 2014, an event that did bring out the entire community.  While, we can muse about who actually comes to these events – they involve public money so therefore should be accessible and attended by all sections of society, right? – we don’t actually know for sure. This was the purpose of some work that I did with Matt Whittle and Nik Lomax last summer.  We worked with LCC on some very tasty data that was collated throughout Le Grand Depart.  The findings do indeed back up what you would expect, typically those who came to view the race fall into the category commonly labelled as MAMILS (Middle-aged men in lycra), this was particularly prevalent at the King of the Mountains sections.  Further details about this work can be found in the very catchy sounding Conversation article: Charge of the lycra brigade.

Space, the final frontier…

In the fastest ever journal submission to publication I have ever experienced, the following paper has just been published online, and free to grab a copy of:

“Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?

It is co-written with Nick Malleson and Andrew Crooks.

Here is the abstract to whet your appetite:


Cities are complex systems, comprising of many interacting parts. How we simulate and understand causality in urban systems is continually evolving. Over the last decade the agent-based modeling (ABM) paradigm has provided a new lens for understanding the effects of interactions of individuals and how through such interactions macro structures emerge, both in the social and physical environment of cities. However, such a paradigm has been hindered due to computational power and a lack of large fine scale datasets. Within the last few years we have witnessed a massive increase in computational processing power and storage, combined with the onset of Big Data. Today geographers find themselves in a data rich era. We now have access to a variety of data sources (e.g., social media, mobile phone data, etc.) that tells us how, and when, individuals are using urban spaces. These data raise several questions: can we effectively use them to understand and model cities as complex entities? How well have ABM approaches lent themselves to simulating the dynamics of urban processes? What has been, or will be, the influence of Big Data on increasing our ability to understand and simulate cities? What is the appropriate level of spatial analysis and time frame to model urban phenomena? Within this paper we discuss these questions using several examples of ABM applied to urban geography to begin a dialogue about the utility of ABM for urban modeling. The arguments that the paper raises are applicable across the wider research environment where researchers are considering using this approach.

Question is, what famous line to try and get into the title of a paper next time..?

The Future of Geocomputation Workshop

Just returning from a workshop on Geocomputation at Kings College London.  The event was put together to bring researchers together from around the country to discuss the ‘future of Geocomputation’.  There were three keynotes (Chris Brundson, Alex Singleton and myself) each giving our different views on the future of Geocomputation.  Whilst we concentrated on different aspects (technology, in particular agent-based modelling for me, Bayesian approach called ABC for Chris and teaching of GIS for Alex), there was commonality in the areas that we felt future work was needed in such as data handling, visualisation, more engaging teaching methods and teaching programming to students.  For me, the future of Geocomputation is very much going to be shaped by developments in both agent-based modelling and big data.  Instead of developing agent frameworks (of which there are numerous – I did a head count of about 86), we should instead focus on tackling the thorny issues of identifying behaviour and processes in systems as well as calibration and validation.


This is something I will return to in a future post, but a copy of my slides can be found by clicking on Heppenstall.

ABM and urban economics

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New paper just published… Olner D; Evans A; Heppenstall A (2015) An agent model of urban economics: Digging into emergence, Computers, Environment and Urban Systems, . doi: 10.1016/j.compenvurbsys.2014.12.003 Abstract This paper presents an agent-based ‘monocentric’ model: assuming only a fixed location for firms, outcomes … Continue reading