Agent-Based Modeling Chapter

In the recently published "Comprehensive Geographic Information Systems" edited by Bo Huang, Alison Heppenstall, Nick Malleson and myself have a chapter entitled "Agent-based Modelling"¹. Within the chapter, we provide a overview of agent-based modeling (ABM) especially for the geographical sciences. This includes a section on how ABM emerged i.e. "The Rise of the (Automated) Machines", along with a discussion on what constitutes an agent. This is followed with steps to building an agent-based model, including: 1) the preparation and design; 2) model implementation 3) and how one goes about evaluating a model (i.e. verification, calibration and validation and how these are particularity challenging with respect to spatial agent-based models). We then discuss how we can integrate space and GIS into agent-based models and review a number of open-source ABM toolkits (e.g. GAMA, MASON, NetLogo) before concluding with challenges and opportunities that we see ahead of us, such as adding more complex behaviors to agent-based models, and how "big data" offers new avenues for multiscale calibration and validation of agent-based models.  If you are still reading this, below you can read the abstract of the paper and find the full reference to the chapter.

Abstract:

Agent-based modeling (ABM) is a technique that allows us to explore how the interactions of heterogeneous individuals impact on the wider behavior of social/spatial systems. In this article, we introduce ABM and its utility for studying geographical systems. We discuss how agent-based models have evolved over the last 20 years and situate the discipline within the broader arena of geographical modeling. The main properties of ABM are introduced and we discuss how models are capable of capturing and incorporating human behavior. We then discuss the steps taken in building an agent-based model and the issues of verification and validation of such models. As the focus of the article is on ABM of geographical systems, we then discuss the need for integrating geographical information into models and techniques and toolkits that allow for such integration. Once the core concepts and techniques of creating agent-based models have been introduced, we then discuss a wide range of applications of agent-based models for exploring various aspects of geographical systems. We conclude the article by outlining challenges and opportunities of ABM in understanding geographical systems and human behavior.

Keywords: Agent-based modeling; Calibration; Complexity; Geographical information science; Modeling and simulation; Validation; Verification.

Full Reference: 

Crooks, A.T., Heppenstall, A. and Malleson, N. (2018), Agent-based Modelling, in Huang, B. (ed), Comprehensive Geographic Information Systems, Elsevier, Oxford, England. Volume 1, pp. 218-243 DOI: https://doi.org/10.1016/B978-0-12-409548-9.09704-9. (pdf)

^{1. [Readers of this blog might of expected the chapter would be about Agent-based Modeling, but its still worth a read!]↩}

Call for Papers: Geosimulation and Its Emerging Directions with AI

As part of the GeoAI and Deep Learning Symposium at the 2026 AAG Annual Meeting in San Francisco, California we have a call for papers for sessions entitled "Geosimulation and Its Emerging Directions with AI"

Call for Papers:

Simulating past, present, and future events can empower humans to understand the composition and interactions in complex systems and explain their emergence and evolution from bottom up. In practice, geosimulations constitute a powerful tool in engaging different stakeholders, exploring what-if scenarios, and evaluating alternative policy outcomes.

We invite interdisciplinary works for the exploration and understanding of complex social and environmental processes by means of computer simulation. We focus on all aspects of simulation and agent societies, including multi-agent systems, agent-based modeling, microsimulation, artificial intelligence (AI) agents, and the integration of Generative AI with simulation.

As GenAI is impacting all aspects of our lives, we are wondering how it will impact geospatial simulations. How do multimodal large language models (MLLMs) help with agent-decision making in the form of generating agent-personas or scheduling agent activities? Can MLLMs reduce coding barriers for beginners? Will GenAI lead to a new generation of modeling toolkits? What are the challenges brought by MLLMs in model design, validation, and computing costs?

We welcome a wide range of studies exploring simulation theories, data, methodologies, and frameworks. We are also interested in case studies applying geosimulations to address real-world challenges. Potential topic areas include, but are not limited to:

• Geosimulation Models and Applications
• Conceptual Geosimulation Models
• General-Purpose Geosimulation Framework
• AI and Geosimulation
• Agents’ Behaviors, Decision-making and AI Agents
• Data Generation Framework
• Validation and Verification for Geosimulation
• Digital Twins
• Microsimulation
• Multi-agent Systems

If you are interested, please email your title and 250-word abstract to Fuzhen Yin (fyin@uccs.edu) and Jeon-Young Kang (geokang@khu.ac.kr) by October 30th.

Chairs:

• Fuzhen Yin, University of Colorado Colorado Springs
• Jeon-Young Kang, Kyung Hee University

Organizers:

• Alison Heppenstall, University of Glasgow, Scotland.
• Andrew Crooks, University at Buffalo, USA.
• Na (Richard) Jiang, Hong Kong University of Science and Technology (Guangzhou), China
• Fuzhen Yin, University of Colorado, Colorado Springs, USA.
• Raja Sengupta, McGill University, Canada.
• Suzana Dragicevic, Simon Fraser University, Canada.
• Boyu Wang, University at Buffalo, USA.
• Sarah Wise, University College London, England
• Jeon-Young Kang, Kyung Hee University, South Korea
• Yahya Gamal, University of Glasgow, Scotland.
• Alexander Michels, University of Texas at Dallas, USA
• Joon-Seok Kim, Emory University, USA

Sponsor Groups:

• Cyberinfrastructure Specialty Group, 
• Geographic Information Science and Systems Specialty Group, 
• Spatial Analysis and Modeling Specialty Group

Modeling Forced Migration

At the upcoming Annual Modeling and Simulation Conference (ANNSIM) we have several papers being presented. One of which is with Troy Curry and Arie Croitoru entitled "Modeling Forced Migration: A System Dynamic Approach." In this paper we study how forced migration can be modeled through a systems dynamics perspective. 

 

To some extent this  paper builds upon our previous work on refugees especially making use new open data sources that allow us to study forced migration. Using ideas from  systems thinking which incorporates notions  non-linearity, interconnectedness, relationships, causality and feedbacks we build a systems dynamics model of the Syrian refugee crisis from January 2012 until December 2018. The model itself  explores refugee-producing variables that have been linked as determinants of forced migration including human rights violations, political violence, generalized violence, and civil war. We use these refugee-producing variables  to simulate the flow of refugees from Syria to Greece, Turkey, Lebanon and Jordan. 

 

If this sounds of interest, below you can read the abstract of the model, see a high-level causal loop diagram for our forced migration model along with our validation attempts  such as comparing predicted system dynamics model refugee counts vs. reference United Nations High Commissioner for Refugees (UNHCR) refugee counts. We also have included a movie of one such model scenario however,  readers can also run the model here. Finally at the bottom of the page you can find the full reference to paper along with a link to a pre-print.

Abstract: 

Forced migration of populations is a topic of increasingly national and international importance due to security, international relations, and humanitarian considerations. Despite its importance, there has been a dearth of quantitative research to support modeling and simulation of this topic, thus hindering our ability to better understand this phenomenon. Motivated by this gap, this research leverages the recent availability of diverse set of data related to forced migration, including regime legitimacy, violence, human rights violations, conflict, socio-political mobilization, intervening opportunities, and social media. The purpose of this article is to explore the applicability and utility of open-source data in a system dynamics model to forecast population displacement, and to illustrate the benefits of using a system dynamics approach to modeling displaced population on a national and international scale. Our results suggest that this proposed approach can be used to understand such migration processes and simulate possible scenarios.

Keywords: forced migration, refugee, system dynamics, prediction model, Middle East.

High-level causal loop diagram for forced migration.

Migration routes in simulation (i.e., Greece, Turkey, Lebanon, Jordan).

Simulation refugee counts for paths to different countries (i.e., Greece, Turkey, Lebanon, Jordan).

Model validation - comparing predicted system dynamics model refugee counts vs. reference UNHCR refugee counts.

Full reference:

Curry, T., Croitoru, A. and Crooks, A.T. (2023), Modeling Forced Migration: A System Dynamic Approach, The Annual Modeling and Simulation Conference (ANNSIM), Hamilton, ON. (pdf)

Future Developments in Geographical Agent-Based Models: Challenges and Opportunities

Its been a while since (to say the least), that we wrote a position paper about agent-based modeling. But with agent-based modeling becoming more widely accepted  and the growth of machine learning within the geographical sciences we thought we would revisit some of the existing challenges  (e.g. validation, representing behavior) and discuss how machine learning and data might help here. To this end, Alison Heppenstall,  Nick Malleson, Ed Manley, Jiaqi Ge and Mike Batty, have recently published a paper entitled "Future Developments in Geographical Agent-Based Models: Challenges and Opportunities" in Geographical Analysis.  Below we provide the abstract to the paper, and if this is of interest please follow the links to the paper itself.

Abstract

Despite reaching a point of acceptance as a research tool across the geographical and social sciences, there remain significant methodological challenges for agent-based models. These include recognizing and simulating emergent phenomena, agent representation, construction of behavioral rules, calibration and validation. Whilst advances in individual-level data and computing power have opened up new research avenues, they have also brought with them a new set of challenges. This paper reviews some of the challenges that the field has faced, the opportunities available to advance the state-of-the-art, and the outlook for the field over the next decade. We argue that although agent-based models continue to have enormous promise as a means of developing dynamic spatial simulations, the field needs to fully embrace the potential offered by approaches from machine learning to allow us to fully broaden and deepen our understanding of geographical systems.

Full Reference:

Heppenstall, A., Crooks, A.T., Malleson, N., Manley, E., Ge, J. and Batty, M. (2021), Future Developments in Geographical Agent-Based Models: Challenges and Opportunities, Geographical Analysis. https://doi.org/10.1111/gean.12267 (pdf)

Improving Evidence Based Policy Decisions

Improving Evidence Based Policy Decisions: Piloting the Application of Advanced Computer Modelling Techniques to Real Life Policy Problems

The other day we attended a workshop organised by Georgios Theodoropoulos from the University of Birmingham called Improving Evidence Based Policy Decisions

We gave a talk entitled ‘Validating and Verifying Agent-Based Models for Planning and Public Policy Analysis’ which focused around validation and verification of ABM (issues which will be explored in later posts). The presentation highlighted how urban modelling has changed, especially how we conceptualise systems; a move from aggregate, to disaggregate; focusing on change not equilibrium, where dynamics has come to the fore. Thus a crucial issue is how do we know how good this new class of models is in terms of their fit to reality? Do we even need to worry about this any longer? These issues where explored using ABM developed at CASA from fine scale pedestrian models to more aggregate models examining residential segregation and urban sprawl.

Other talks examined the role data driven simulation for housing policy which is part of the Adaptive Intelligent Model-Building for the Social Sciences using Symbiotic Simulation (AIMSS) project. While Mark Birkin gave a talk entitled ‘Issues in the specification and validation of a complex socio-demographic simulation model’ which showed the MoSeS (Modelling and Simulation for e-Social Science) project from the University of Leeds which aims to develop a demographic simulation at the level of individuals and households to give robust forecasts of the future population of the UK based on microsimulation techniques but in a dynamic context.

A copy of the presentation Mike Batty and I gave can be downloaded by clicking here. Any comments more than welcome.

For details of other talks (including pdfs) see the National Centre for e-Social Science (NCeSS) website

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

We have just finished writing a working paper entitled “Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations”

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.

Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded.

Key Words: Agent-Based Modelling (ABM), agent-based models, geospatial / spatially explicit modelling, verification, calibration, validation, Geographical Information Systems (GIS), linkage (coupling or embedding / integration).

The paper is available for download at the CASA website under working papers. Alternatively click here.

Full Reference: 

Castle, C. J. E. and Crooks, A. T. (2006), Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations, Centre for Advanced Spatial Analysis (University College London): Working Paper 110, London, England. (pdf)

Big Data, Agents and the City

In the recently published book "Big Data for Regional Science" edited by Laurie Schintler and  Zhenhua Chen, Nick Malleson, Sarah Wise, and Alison Heppenstall and myself have a chapter entitled: Big Data, Agents and the City. In the chapter we discuss how big data can be used with respect to building more powerful agent-based models. Specifically how data from say social media could be used to inform agents behaviors and their dynamics; along with helping with the calibration and validation of such models with a emphasis on urban systems. 

Below you can read the abstract of the chapter, see some of the figures we used to support our discussion, along with the full reference and a pdf proof of the chapter. As always any thoughts or comments are welcome.

Abstract:

Big Data (BD) offers researchers the scope to simulate population behavior through vastly more powerful Agent Based Models (ABMs), presenting exciting opportunities in the design and appraisal of policies and plans. Agent-based simulations capture system richness by representing micro-level agent choices and their dynamic interactions. They aid analysis of the processes which drive emergent population level phenomena, their change in the future, and their response to interventions. The potential of ABMs has led to a major increase in applications, yet models are limited in that the individual-level data required for robust, reliable calibration are often only available in aggregate form. New (‘big’) sources of data offer a wealth of information about the behavior (e.g. movements, actions, decisions) of individuals. By building ABMs with BD, it is possible to simulate society across many application areas, providing insight into the behavior, interactions, and wider social processes that drive urban systems. This chapter will discuss, in context of urban simulation, how BD can unlock the potential of ABMs, and how ABMs can leverage real value from BD.  In particular, we will focus on how BD can improve an agent’s abstract behavioral representation and suggest how combining these approaches can both reveal new insights into urban simulation, and also address some of the most pressing issues in agent-based modeling; particularly those of calibration and validation.

Keywords: Agent-based models, Big Data, Emergence, Cities.

The growth in Agent-based modeling -from search results of Web of Science and Google Scholar.

Hotspots of activity of Tweeter Users: Tweet locations and associated densities for a selection of prolific users.

Full Reference:

Crooks, A.T., Malleson, N., Wise, S. and Heppenstall, A. (2018), Big Data, Agents and the City, in Schintler, L.A. and Chen, Z. (eds.), Big Data for Urban and Regional Science, Routledge, New York, NY, pp. 204-213. (pdf)

Geosimulation Models - AAG 2014: Call for Papers

GEOSIMULATION MODELS

DESCRIPTION OF THE SESSION(S)

Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to mature as methodologies to explore a wide range of geographical and more broadly social sciences problems facing society. The aim of these sessions is to bring together researchers utilizing geosimulation techniques (and associated methodologies) to discuss topics relating to: theory, technical issues and applications domains of ABM and CA within geographical systems.

Papers will discuss issues relating to:

• Validation, verification and calibration of Agent-based and CA models
• Hybrid modeling approaches (e.g. utilizing Spatial Interaction, Microsimulation, etc.)
• Handling scale and space issues
• Visualization of agent-based models (along with their outputs)
• Ways of representing behavior within models of geographical systems
• Participatory modeling and simulation
• Applications: Ranging from the micro to macro scale

Please e-mail the abstract and key words with your expression of intent to Andrew Crooks by November 28th, 2013. Please make sure that your abstract conforms to the AAG guidelines in relation to title, word limit and key words and as specified at http://www.aag.org/cs/annualmeeting/call_for_papers;. An abstract should be no more than 250 words that describes the presentation's purpose, methods, and conclusions as well as to include keywords. Full submissions will be given priority over submissions with just a paper title.

ORGANIZERS:
Andrew Crooks, Computational Social Science, George Mason University.
Suzana Dragicevic, Department of Geography, Simon Fraser University.
Paul Torrens, Department of Geographical Sciences and Institute for Advanced Computer Studies, University of Maryland.

TIMELINE:
September 30th, 2013: First call for papers.
November 19th, 2013: Second call for papers


November 28th, 2013: Abstract submission and expression of intent to session organizers. 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. Full submissions will be given priority over submissions with just a paper title.

November 29th, 2013: Session finalization. Session organizers determine session order and content and notify authors.

December 2st, 2013: Final abstract submission to AAG, via www.aag.org. 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.

December 3rd, 2013: AAG registration deadline. Sessions submitted to AAG for approval.

April 8th -12th, 2014: AAG meeting, Tampa Bay, Florida, USA.

Call for Abstracts: Geosimulations for Addressing Societal Challenges

As part of the The 10th Anniversary Symposium on Human Dynamics Research which will take place at the 2024 American Association of Geographers (AAG) Annual Meeting in Honolulu, Hawaii  between Tuesday, April 16 – Saturday, April 20, 2024 we are organizing a session(s) on Geosimulations for Addressing Societal Challenges. If the session description is of interest, please feel free to submit an abstract (details are below).

Session Description:

There is an urgent need for research that promotes sustainability in an era of societal challenges ranging from climate change, population growth, aging and wellbeing to that of pandemics. These need to be directly fed into policy. We, as a Geosimulation community, have the skills and knowledge to use the latest theory, models and evidence to make a positive and disruptive impact. These include agent-based modeling, microsimulation and increasingly, machine learning methods. However, there are several key questions that we need to address which we seek to cover in this session. For example, What do we need to be able to contribute to policy in a more direct and timely manner? What new or existing research approaches are needed? How can we make sure they are robust enough to be used in decision making? How can geosimulation be used to link across citizens, policy and practice and respond to these societal challenges? What are the cross-scale local trade-offs that will have to be negotiated as we re-configure and transform our urban and rural environments? How can spatial data (and analysis) be used to support the co-production of truly sustainable solutions, achieve social buy-in and social acceptance? And thereby co-produce solutions with citizens and policy makers.

We are particularly interested in presentations that will discuss issues relating to:

• Agent-based modeling and microsimulation techniques for responding to societal challenges; Agent-based models used for policy formation;
• Data driven modeling;
• Utilizing machine modeling for geosimulation;
• Creating really big models using exascale computation;
•  Model validation and assessment; 
• Participatory methods for agent-based modeling;
• Approaches to connect and share (open source) data and models;
• Revealing, quantifying, and reducing socio-economic inequalities with Geosimulation.

Next Steps:

If this sounds of interest, please e-mail the abstract and key words with your expression of intent to Richard Jiang (njiang8@buffalo.edu) by November 9th (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: https://aag.secure-platform.com/aag2024/page/abstracts/abstract-guidelines

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

Timeline:

• 9th November, 2023: Abstract submission deadline. E-mail Richard Jiang by this date if you are interested in being in this session. Please submit an abstract and key words with your expression of intent.
• 14th November, 2023: Session finalization and author notification
• 15th November, 2023: Final abstract submission to AAG, via https://aag.secure-platform.com/aag2024/. 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 Richard Jiang. Neither the organizers nor the AAG will edit the abstracts. 
• 16th November, 2023: AAG registration deadline. Sessions submitted to AAG for approval.
• 16th -20th April 2024: AAG in Honolulu.
  

Organizers

• Alison Heppenstall, University of Glasgow, Scotland.
  
• Na (Richard) Jiang, University at Buffalo, USA.
• Gary Polhill, The James Hutton Institute, Scotland.
• Andrew Crooks, University at Buffalo, USA.
• Raja Sengupta, McGill University, Canada.
  
• Suzana Dragicevic, Simon Fraser University, Canada. 
• Sarah Wise, University College London, England. 
• Jeon-Young Kang, Kyung Hee University, South Korea.
  

Call for Papers: 9th European Social Simulation Association Conference

9th European Social Simulation Association Conference
Warsaw School of Economics, Warsaw, Poland
September 16-20, 2013

The European Social Simulation Association and Warsaw School of Economics, Division of Decision Analysis and Support, invite researchers and scholars interested in applications and theoretical foundations of simulation modeling in social sciences to participate in the 9th European Social Simulation Association Conference.

The conference aims to provide an interdisciplinary forum for social scientists, theorists, applied researchers and simulation modelers to cooperate and exchange ideas concerning state of the art in methods and applications of computational social sciences.

Scope and Interests

The topics of interest include, but are not limited to:

• Applications of agent-based modeling in social sciences
• Agent-based computational economics & finance
• Conflict resolution & cooperation
• Coupled human-natural systems
• Diffusion of innovations
• Dynamics of trust, social norm, structures, reputation & opinion
• Epidemiology & pharmacoeconomics
• Group decisions & collective behaviors
• Market design, mechanism design & auctions
• Privacy, safety & security
• Public policy & regulatory issues
• Resource management, environmental practices & policy
• Social emergence & evolution of institutions
• Social media and volunteered information
• Social networks and their dynamics

• Tools and methods for development of simulation models 
• Advanced distributed computing
• Agent ontologies
• Agent-embodied Artificial Intelligence
• Model replication, verification & validation
• Participatory & Human-in-the-Loop simulations
• Simulation software & programming computational frameworks

• Techniques for visualizing, interpreting and analyzing simulation outputs
• Coupling simulations and optimization methods
• Data analysis software for simulations
• Experiment design and data farming for simulations
• Simulation metamodels
• Statistical & data mining techniques for simulated data

Submission

• Full paper - in the length of 10 to 12 pages, which should be comprehensive and consists of detailed presentation of theory, methodology and simulation results
• Extended abstract - in the length of 3 to 4 pages, which presents the current topic in progress with enough detail to ensure proper evaluation
• Poster - should present the current work in progress

 Contributions can be submitted to general session or the following special tracks:

• Adaptive behavior , social interactions and global environmental change: an agent-based perspective (chairs: T. Filatova, G. Polhill, R. van Duinen)
• Applications of computational social science in conflict and sensitive contexts (chair: A. Geller)
• Business applications of computational social science (chair: M. Łatek)
• Heterogeneity and interaction in macroeconomic modeling (chair: G. Koloch)
• Social simulation of science processes (chair: F. Squazzoni)
• Statistical analysis of simulation models (chair: B. Kamiński)
• Using qualitative rules to inform behavioral rules (chair: B. Edmonds)

Important dates

• Registration opens: 1 January 2013
• Paper submission closes: 1 March 2013
• Notification of acceptance: 15 April 2013
• Final manuscript due: 15 May 2013

Paper publication

• Accepted full papers will be published by Springer in the conference proceedings series "Advances in Intelligent Systems and Computing", http://www.springer.com/series/11156 (indexed by ISI Proceedings, DBLP, Ulrich's, EI-Compendex, SCOPUS, Zentralblatt Math, MetaPress, Springerlink).
• Authors of selected full papers or extended abstracts will be invited to submit their extended version for special issue of Central European Journal of Economic Modelling and Econometrics, http://cejeme.org/ (indexed by IndexCopernicus, IC Value in 2011: 4.85 and RePEc).
• Full paper abstracts, extended abstracts and poster summaries will be presented on conference website.

Local organizing committee contact: contact@essa2013.org
Conference website: http://www.essa2013.org

ABMUS2017: The 2nd International Workshop on Agent-based modelling of urban systems

Call for Papers: The 2nd International Workshop on Agent-based modelling of urban systems

The ABMUS2017 workshop on Agent-based modelling of urban systems will be held at the AAMAS2017 conference in Sao Paulo, Brazil on 8-9 May 2017. It is the follow-up of ABMUS2016 held in Singapore during AAMAS2016 on the 10th of May 2016.

Researchers and practitioners who use agent-based models and agent systems to understand, explore, and manage cities and urban infrastructure systems are invited to submit papers to ABMUS2017. The overarching theme for the workshop is data for agent-based models. Data is essential for building, calibrating, and validating agent-based city and urban infrastructure models. But which approaches are optimal for what purposes? We invite presentations that describe data collection and data management approaches in agent-based models, as well as the use of data sets and methodologies that can be translated and re-used between researchers, sectors and countries.

Workshop topics include, but are not limited to, the following:

• Large scale urban simulation applications
• Agent-based modelling of urban transport, land-use, housing, energy, health, etc.
• Spatially explicit micro-simulation modelling
• Simulation of household behaviour and technology adoption
• Localized population synthesis
• Multi-scale urban systems (temporal and spatial)
• Social simulation of demographic transitions
• Use of mobile technology to validate activity patterns
• Techniques for integrating independently developed components
• Agent-based platforms for urban simulation
• Data structures for simulating urban environments
• (Multi-)agent systems for decision support in e.g. transport, energy use and air quality
• Connection of simulation models to social and geographical theory
• Development of 'master' city datasets for model validation

At the workshop each presenter will be given 10 minutes to introduce their paper and/or case study, followed by 5-10 minutes in which presenters will share their views on the data for agent-based models theme. After three presentations there will be 20-30 minutes of group discussion in which presenters will act as panel members.

Important dates:

• 7 February 2017: Deadline for paper submissions
• 2 March 2017: Notification of acceptance following the review process
• 17 March 2017: Deadline for submitting camera-ready papers (including LaTeX files)
• 8-9 May 2017: ABMUS workshop at the AAMAS2017 conference in Sao Paulo, Brazil

For details on how to submit please see http://modelling-urban-systems.com/ or for more information please contact:

• Koen van Dam -- k.van-dam@imperial.ac.uk
• Jason Thompson -- jason.thompson@unimelb.edu.au

The organizing committee consists of:

• Dr Koen H. van Dam, Imperial College London
• Dr Jason Thompson, University of Melbourne
• Prof Pascal Perez, University of Wollongong
• Dr Nick Malleson, University of Leeds
• Prof Alison Heppenstall, University of Leeds
• Dr Andrew Crooks, George Mason University
• Dr Claudia Pelizaro, University of Melbourne

Agent-Based & Cellular Automata Models for Geographical Systems @ the AAG

If you attending the AAG Annual Meeting this year, please feel free to come to our sessions entitled Agent-Based and Cellular Automata Models for Geographical Systems.

LOCATION AND DATE

Saturday, April 13th, from 8:00 AM to 6:00 PM in Angeleno, The LA Hotel, Level 2  

DESCRIPTION OF THE SESSIONS

The use of Agent-based Modeling (ABM) and Cellular Automata (CA) models within geographical systems are starting to mature as methodologies to explore a wide range of geographical and more broadly social sciences problems facing society. The aim of these sessions is to bring together researchers utilizing agent-based models, CA (and associated methodologies) to discuss topics relating to: theory, technical issues and applications domains of ABM and CA within geographical systems.

Papers will discuss issues relating to:

• Validation, verification and calibration of Agent-based and CA models
• Hybrid modeling approaches (e.g. utilizing Spatial Interaction, Microsimulation, etc.)
• Handling scale and space issues
• Visualization of agent-based models (along with their outputs)
• Ways of representing behavior within models of geographical systems
• Participatory modeling and simulation
• Applications: Ranging from the micro to macro scale

ORGANIZERS:
Christopher Bone, Department of Geography, University of Oregon.
Andrew Crooks, Computational Social Science, George Mason University.
Suzana Dragicevic, Department of Geography, Simon Fraser University.
Alison Heppenstall, School of Geography, University of Leeds.
Michael Batty, Centre for Advanced Spatial Analysis (CASA), University College London.
Amit Patel, School of Public Policy, George Mason University.

SPONSORSHIPS:
Geographic Information Science and Systems Specialty Group and the Spatial Analysis and Modeling Specialty Group

SESSION OUTLINES:

5150: 1: Methodological Advances (8:00 AM)

Kirk Harland and Mark Birkin

• Using Synthetically Generated Populations in Agent-Based 

David O'Sullivan and George  Perry 

• Towards a 'Pattern Language' for Spatial Simulation 

James Millington, David O'Sullivan and George  Perry 

• Narrative explanation in agent-based modelling 

Christopher Bone

• A Spatiotemporal Analytical Framework for Agent-based Modeling 

Anthony Jjumba and Suzana Dragicevic

• Multi-dimensional Automata Model for the Simulation of Pollutant Diffusion

5250 Land-Use Models (10:00 AM)

Jan Baetens and Bernard De Baets

• Towards real-time GIS-based modeling of wildfires

Haiyan Zhang and Clinton Andrews

• Modeling land market's responses to climate change in the coastal zone

Moira Zellner, Daniel Milz, Leilah Lyons, Lissa Domoracki and Joshua Radinsky

• Participatory agent-based modeling for environmental planning: How stakeholders (cannot) resolve the dissonance between complexity and beliefs

Atesmachew Hailegiorgis

• Agent-Based Modeling of Climate Change Adaptation in Southern Ethiopia

Amit Patel,  Andrew Crooks and Naoru Koizumi

A Spatial ABM Approach to Explore Slum Formation Dynamics in Ahmedabad, India

5450 Applications (2:00 PM)

Bianica Pint and Andrew Crooks

• The Impact of a Slum's Social Dynamics and Geospatial Landscape on the Emergence of Riots: The Case of Kibera 

Ali Afshar Dodson

• Simulating Social Segregation

Rongxu Qiu, Wei Xu and Shan Li

• Agent-based simulation of the spatial diffusion of tourist flow

Sarah Wise

• Hotspots: Simulating the 2012 Colorado Wildfires

Majeed Pooyandeh and Danielle Marceau 

• A web/agent-based model to simulate the negotiation process of stakeholders in the Elbow River watershed in Alberta

5550 Applications (4:00 PM)

Arnaud Banos, Sonia Chardonnel,  Christophe Lang,  Nicolas Marilleau and Thomas Thevenin 

• Towards more sustainable cities: coupling actors and agents in a serious game 

Ed Manley and Tao Cheng

• Incorporating Heterogeneous Spatial Cognition into Urban Road Transportation Simulation - What Improvement on Conventional Methods?

Yong Yang, Ana  Diez-Roux,  Amy Auchincloss, Daniel Rodriguez, Daniel Brown and Rick Riolo

• The use of an agent-based model of utilitarian walking in adults to examine the impact of various interventions on population walking 

Andrew Crooks and Atesmachew Hailegiorgis

• Modeling the Spread of Cholera within Refugee Camps: An Agent-based Modeling Approach

Timothy Gulden and  Joseph Harrison

• Modeling Cities and Displacement through an Agent-based Spatial Interaction Model

Book Review: The Dynamics of Complex Urban Systems

I just finished reading "The Dynamics of Complex Urban Systems: An Interdisciplinary Approach" edited by Albeverio, S., Andrey, D., Giordano, P. and Vancheri, A. and I thought I would share my thoughts about it.

As we are all aware, cities play a crucial role in our lives, providing habitats for over half of the world?s population. However, understanding such systems is extremely complex as they are composed of many parts, with many dynamically changing parameters and large numbers of discrete actors interacting within space. The heterogeneous nature of cities makes it difficult to generalise localised problems from that of citywide problems. As Wilson (2000) writes, such understanding of cities represents "one of the major scientific challenges of our time". Such understanding how cities function is of crucial importance if we are attempting to tackle problems that such systems face (e.g. urban sprawl, congestion, segregation, etc.) or to make them more sustainable for future generations of inhabitants. One has to understand the complex interactions between urban systems in terms of internal factors (e.g. from the decisions of individuals such as deciding where to locate) to more external factors (such as international economics) along with social developments. Such underlying process can be slow or fast, acting locally or globally. Most urban theory until now has been based on the assumption of slowly varying spatial and social structures. However these notions are now being questioned giving rise to various types of models, such as those employing dissipative dynamics, stochastic cellular automata and agent-based models, fractal geometry, and evolutionary change models, and to further mathematically oriented approaches. In "The Dynamics of Complex Urban Systems", Albeverio et al. (2008) present a range of articles from leading scholars focusing on the above types of models and how approaches developed by different communities can be used to study urban systems and thus gain a greater understanding of how such systems operate.

"The Dynamics of Complex Urban Systems" book is a result of an international workshop which had clear sessions ranging from general dynamical models (e.g. urban growth, pedestrian dynamics), models from economics and models for megacities (e.g. large-scale city formation, socio dynamics), models from information science and data management (e.g. data mining, GIS, data availability), related mathematical and physical theories and models (e.g. neural networks, power laws and phase transitions), models of calibration/validation and forecasts (e.g. comparison of empirical data and simulations), and dynamical models and case studies of real world systems. The chapters presented within this book are arranged alphabetically because the editors of the book believed that there was much overlap between the sessions and the subsequent papers. The only exception is that of the first chapter by Mike Batty entitled "Fifty Years of Urban Modelling: Macro-Statics to Micro-Dynamics" which provides an extensive, chronological and conceptual overview of urban modelling over the last fifty years in the context of current developments and which subsequent chapters explore in greater depth. From reading the edited book this is a well-made decision by the editors. Many of the chapters cross many of the sessions and range from modelling individual movement such as pedestrian models through to traffic simulations and transport networks to the study of systems of cities and innovation processes along the way linking socio-economic and cultural factors (such as employment and housing) to various types of models.

Overall the book is well written and makes a good source of reference of current research, specifically for those interested in studying urban systems using a variety of computational modelling approaches. Furthermore, the book highlights the need for cross-disciplinary research between the natural (e.g. physics, mathematics, computer science, biology, etc) and regional sciences (e.g. geography, economics, architecture, etc) with respect to improving our understanding of the complexities seen within urban systems and how such systems operate.

References

Albeverio, S., Andrey, D., Giordano, P. and Vancheri, A. (Eds.)(2008), The Dynamics of Complex Urban Systems: An Interdisciplinary Approach, Physica-Verlag Heidelberg, NY.

Wilson, A.G. (2000), Complex Spatial Systems: The Modelling Foundations of Urban and Regional Analysis, Pearson Education, Harlow, UK.

MASON Update

At the upcoming Multi-Agent-Based Simulation (MABS) workshop, we have a paper entitled "The MASON Simulation Toolkit: Past, Present, and Future" in which we discuss MASON's development history, its design and (probably more interesting) where MASON is going. This includes:

1. Making it more robust (i.e. easier to run parameter tests), 
2. Making it distributed in order to  run large scale models including geographical explicit ones along for optimization and validation purposes.
3. Making it more coder-friendly by adding code templates that allow users to generate code skeletons for common MASON patterns and a way to easily record outputs and statistics.
4. Making it more community-friendly by hopefully developing a special online repository to enable researchers to distribute models as jar files along with education aids and examples. Relating to this last point we have added a number of example models (code and data) from our own research to GitHub, see: https://github.com/eclab/mason/tree/master/contrib/geomason/sim/app/geo and the data to run the models is either there or here https://cs.gmu.edu/~eclab/projects/mason/extensions/geomason/geodemodata.zip (note this is 1.5 GB).

Below you can read the abstract from the paper along with a link to the paper itself.

Abstract

MASON is a widely-used open-source agent-based simulation toolkit that has been in constant development since 2002. MASON’s architecture was cutting-edge for its time, but advances in computer technology now offer new opportunities for the ABM community to scale models and apply new modeling techniques. We are extending MASON to provide these opportunities in response to community feedback. In this paper we discuss MASON, its history and design, and how we plan to improve and extend it over the next several years. Based on user feedback will add distributed simulation, distributed GIS, optimization and sensitivity analysis tools, external language and development environment support, statistics facilities, collaborative archives, and educational tools.

Keywords: Agent-Based Simulation, Open Source, Library

Full Reference:

Luke, S., Simon, R., Crooks, A.T., Wang, H., Wei, E., Freelan, D., Spagnuolo, C., Scarano, V., Cordasco, G. and Cioffi-Revilla, C. (2018), The MASON Simulation Toolkit: Past, Present, and Future, 19th International Workshop on Multi-Agent-Based Simulation (MABS2018), Stockholm, Sweden. (pdf)

This research is supported by the National Science Foundation (Grant 1727303).

Call for papers: Agent-Based & Cellular Automata Models for Geographical Systems @ AAG 2013

AAG 2013 - CALL FOR PAPERS

SPECIAL SESSION(S): Agent-Based & Cellular Automata Models for Geographical Systems

LOCATION AND DATES
Association of American Geographers Annual Meeting
April, 9-13th, 2013, Los Angeles, USA

DESCRIPTION

The use of Agent-based Modeling (ABM) and Cellular Automata (CA) models within geographical systems are starting to mature as methodologies to explore a wide range of geographical and more broadly social sciences problems facing society. The aim of this session(s) is to bring together researchers utilizing agent-based models, CA (and associated methodologies) to discuss topics relating to: theory, technical issues and applications domains of ABM and CA within geographical systems.

We would particularly welcome papers relating to:

• Validation, verification and calibration of Agent-based and CA models
• Hybrid modeling approaches (e.g. utilizing Spatial Interaction, Microsimulation, etc.)
• Handling scale and space issues
• Visualization of agent-based models (along with their outputs)
• Ways of representing behavior within models of geographical systems
• Participatory modeling and simulation
• Applications: Ranging from the micro to macro scale

Please e-mail the abstract and key words with your expression of intent to Andrew Crooks <acrooks2@gmu.edu; by October 15th, 2012. 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 describes the presentation's purpose, methods, and conclusions as well as to include keywords. Full submissions will be given priority over submissions with just a paper title.

ORGANIZERS:
Christopher Bone, Department of Geography, University of Oregon.
Andrew Crooks, Krasnow Institute for Advanced Study, George Mason University, USA.
Suzana Dragicevic, Department of Geography, Simon Fraser University.
Alison Heppenstall, School of Geography, University of Leeds, Leeds, UK .
Michael Batty, Centre for Advanced Spatial Analysis (CASA), University College London, London, UK.
Amit Patel, School of Public Policy, George Mason University, USA.

TIMELINE:

• October 15th, 2012: Abstract submission and expression of intent to session organizers. 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. Full submissions will be given priority over submissions with just a paper title.
• October 18th, 2012: Session finalization. Session organizers determine session order and content and notify authors.
• October 20th, 2012: Final abstract submission to AAG, via www.aag.org. 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.
• October 24th, 2012: AAG registration deadline. Sessions submitted to AAG for approval.
• April, 9-13th, 2013: AAG meeting, Los Angeles, USA

Call for Papers – Computation for Public Engagement in Complex Problems

Call for Papers – Computation for Public Engagement in Complex Problems: From Big Data, to Modeling, to Action 

We welcome paper submissions for our session(s) at the Association of American Geographers Annual Meeting on 9-14 April, 2018, in New Orleans.  

Session Description: In line with one of the major themes of this conference, we explore the opportunities and challenges that geo-computational tools offer to support public engagement, deliberation and decision-making to address complex problems that link human, socioeconomic and biophysical systems at a variety of different spatial and temporal scales (e.g., climate change, resource depletion, and poverty). Modelers and data scientists have shown increasing interest in the intersection between science and policy, acknowledging that, for all the computational advances achieved to support policy and decision-making, these approaches remain frustratingly foreign to the public they are meant to serve. On one hand, there is a persistent gap in the public’s understanding of and reasoning about complex systems, resulting in unintended and undesirable consequences. On the other hand, there is significant public skepticism about the knowledge generated by the modeling community and its ability to inform policy and decision-making.

We invite theoretical, methodological, and empirical papers that explore advances in geo-computational approaches, including part or all the process to address complex problems: from data collection and analysis, to the development and use of models, to supporting action with data analysis and modeling. We are interested in any work that contributes towards the overall goal of supporting public engagement and action around complex problems, including—but not limited to—the following topics:

• epistemological perspectives; 
• extracting behavioral rules from novel and established data sets; 
• innovative applications of complex systems techniques, and 
• addressing the challenge of complex systems model calibration and validation. 

Please e-mail the abstract and key words with your expression of intent to Moira Zellner (mzellner@uic.edu) by October 18, 2017 (one week before the AAG abstract 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: http://annualmeeting.aag.org/submit_an_abstract. An abstract should be no more than 250 words that describe the presentation’s purpose, methods, and conclusions.

 Timeline summary: 

• October 18, 2017: Abstract submission deadline. E-mail Moira Zellner (mzellner@uic.edu) by this date if you are interested in being in this session. Please submit an abstract and key words with your expression of intent. 
• October 23, 2017: Session finalization and author notification. 
• October 25, 2017: Final abstract submission to AAG, via the link above. 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 Moira Zellner. Neither the organizers nor the AAG will edit the abstracts. 
• November 8, 2017: AAG session organization deadline. Sessions submitted to AAG for approval. 
• April 9-14, 2018: AAG Annual Meeting.  

Organizers:

• Moira Zellner, Department of Urban Planning and Policy, University of Illinois at Chicago.
• Andrew Crooks, Department of Computational and Data Sciences, George Mason University 
• Tom Evans, Department of Geography, Indiana University 
• Jeon-Young Kang, Department of Geography, SUNY at Buffalo 
• Jared Aldstadt, Department of Geography, SUNY at Buffalo 
• Arika Ligmann-Zielinska, Department of Geography, Michigan State University

An Integrated Framework of Global Sensitivity Analysis and Calibration for Spatially Explicit ABMs

In the past we have written about the challenges of validation and to some extent the calibration of agent-based models but never really went into much detail about the calibration process. To this end, Jeon-Young Kang, Alexander Michels, Jared Aldstadt, Shaowen Wang and myself recently had a paper published in Transactions in GIS entitled "An Integrated Framework of Global Sensitivity Analysis and Calibration for Spatially Explicit Agent-Based Models." In the paper we have present an integrated framework for global sensitivity analysis and calibration (GSA-CAL), and then apply the framework to a spatially explicit agent-based model of influenza transmission as a case study in the city of Miami, FL. If this sounds of interest, below you can read the abstract to the paper, see some of the figures from the paper including the general workflow and some of the results. At the bottom of the post you can find the full citation and a link to the paper.

Abstract

Calibration of agent-based models (ABMs) is a major challenge due to the complex nature of the systems being modeled, the heterogeneous nature of geographical regions, the varying effects of model inputs on the outputs, and computational intensity. Nevertheless, ABMs need to be carefully tuned to achieve the desirable goal of simulating spatiotemporal phenomena of interest, and a well-calibrated model is expected to achieve an improved understanding of the phenomena. To address some of the above challenges, this article proposes an integrated framework of global sensitivity analysis (GSA) and calibration, called GSA-CAL. Specifically, variance-based GSA is applied to identify input parameters with less influence on differences between simulated outputs and observations. By dropping these less influential input parameters in the calibration process, this research reduces the computational intensity of calibration. Since GSA requires many simulation runs, due to ABMs' stochasticity, we leverage the high-performance computing power provided by the advanced cyberinfrastructure. A spatially explicit ABM of influenza transmission is used as the case study to demonstrate the utility of the framework. Leveraging GSA, we were able to exclude less influential parameters in the model calibration process and demonstrate the importance of revising local settings for an epidemic pattern in an outbreak.

Workflow of global sensitivity analysis and calibration

Study area

Daily activity-based contact network construction

Results from calibration distance-based mobility (DBM): (a) simulated results from an initial model; (b) simulated results from the calibrated model; and (c) sum of RMSE

 

Full Reference:

Kang, J-Y., Michels, A., Crooks, A.T., Aldstradt, J. and Wang, S. (2021), An Integrated Framework of Global Sensitivity Analysis and Calibration for Spatially Explicit Agent-Based Models, Transactions in GIS. https://doi.org/10.1111/tgis.12837 (pdf)