Thursday, August 25, 2016

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 (acrooks2@gmu.edu) 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 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.
  • 27th October, 2016: AAG registration deadline. Sessions submitted to AAG for approval.
  • 5-9th April, 2017: AAG Annual Meeting.

Organizers:
  • 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.

Tuesday, June 28, 2016

Spatial Agent-based Models of Human-Environment Interactions: Spring 2016

During the past spring semester I taught a class entitled "Spatial Agent-based Models of Human-Environment Interactions". As with many of my courses, students were expected to complete a end of semester project, in this case, develop an agent-based model that explores some aspect of related to the course theme of human-environment interactions. Below is a selection of these projects, which ranged from hiking along the Application trail,  to that of exploring the ride-sharing economy, to the spread of diseases, ecosystem recovery modeling and the origins of social complexity. 


I would like to thank the Students of CSS 645: Spatial Agent-based Models of Human-Environment Interactions for their participation in the class.


Wednesday, June 22, 2016

The Geography of Conflict Diamonds: The Case of Sierra Leone

At the forthcoming  2016 International Conference on Social Computing, Behavioral-Cultural Modeling, and  Prediction and Behavior Representation in Modeling and Simulation. we will be presenting a paper is entitled "The Geography of Conflict Diamonds: The Case of Sierra Leone" The abstract and some of the figures from the paper are below. At the bottom of the post you can find the full reference and a link to the paper and model.
In the early 1990s, Sierra Leone entered into nearly 10 years of civil war. The ease of accessibility to the country's diamonds is said to have provided the funding needed to sustain the insurgency over the years. According to Le Billon, the spatial dispersion of a resource is a major defining feature of a war. Using geographic information systems to create a realistic landscape and theory to ground agent behavior, an agent-based model is developed to explore Le Billon's claim. Different scenarios are explored as the diamond mines are made secure and the mining areas are moved from rural areas to the capital. It is found that unexpected consequences can come from minimally increasing security when the mining sites are in rural regions, potentially displacing conflict rather than removing it. On the other hand, minimal security may be sufficient to prevent conflict when resources are found in the city.

Motives and action-guiding motive via the Intensity Analyzer

A visual comparison of model results to actual events. a: Average model results using default parameter values. b: Actual event intensity.




Full Reference:
Pires, B. and Crooks, A.T. (2016), The Geography of Conflict Diamonds: The Case of Sierra Leone, in Xu, K. S., Reitter, D., Lee, D. and Osgood, N. (eds.), Proceedings of the 2016 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, Washington, DC, pp. 335-345. (pdf)
A full description of the model and source code along with the data is available at: https://www.openabm.org/model/4955/

Friday, May 13, 2016

A Semester with Urban Analytics

This past semester I gave a new class at GMU entitled "Urban Analytics". In a nutshell the class was about introducing students to a broad interdisciplinary field that focuses on the use of data to study cities. More specifcally the emphasis of the class was to provide students with a understanding of what methods, tools and theory can be used to monitor, analyze and model cities. 

From my past research and also when preparing the class material,  I have come to the realization that to study cities (like many others, you know who you are) that there is no one general model, tool or dataset. Therefore, one needs to maintain a toolbox of specialized tools than can be applied to different aspects of urban problems and questions. 

The toolbox that we used in class included a variety of software such as ArcGIS, QGIS, GeoDa, SANET along with programing and scripting in Python and R to modeling  cities via UrbanSim, NetLogo and MASON. Data we used ranged from crowdsourced (e.g. volunteered geographical information) data such as from OpenStreetMap or Wikipedia, to crowd harvested (ambient geographical information) data such as Twitter and Flickr, as-well as more traditional sources of data such as the US Census.

The Urban Analytics Toolbox

As an introduction to urban analytics, the course had the following objectives:
  1. to understand the motivation for the use of data to study cities, including some historical aspects; 
  2. to learn about the variety of Urban Analytics research programs across the several disciplines (urban planning, regional science, public policy, geography, computational social science etc.), through a survey of the literature and case studies. 
  3. to understand the distinct contribution that Urban Analytics can make by providing specific insights about cities at multiple scales. 
  4. to provide the foundations for more advanced work in the area of Urban Analytics. 
As with many of my courses, students were expected to complete a end of semester project. Below is a selection of these projects which explored some aspect of urban life.



I would like to thank the students for participating in this new class. It was a fun trip.

Sunday, April 24, 2016

NetLogo Reproduction of Walk This Way

Several months ago, we posted that we had just had a paper accepted entitled "Walk this Way: Improving Pedestrian Agent-Based Models through Scene Activity Analysis. The original model was created in MASON but know it has been reproduced in NetLogo. The purpose of this exercise was to see if the model could be reproduced from the description in said paper along with the availability of the source code and data. Specifically whether there is sufficient information in the paper to reproduce the model and the results. It was an interesting exercise translating methods from MASON into NetLogo procedures (also a lot less lines of code). 


A: NetLogo Graphical User Interface (GUI), B: Original MASON GUI.


In order to really ensure this was a good reproduction it was also necessary to provide the data we compared the results to from the original model (something which is not very common in ABM publications). This way we could could see if the re-implemented model really did match the results of the original model. 


To the left, you can see the graphical user interfaces for the NetLogo model and the original model implemented in MASON.


More information about the re-implementation and the code can be found over at Yang's Blog: http://bit.ly/geospatialcss







Full Reference to the Original Paper:
Crooks, A.T., Croitoru, A., Lu, X., Wise, S., Irvine, J. and Stefanidis, A. (2015),  Walk this Way: Improving Pedestrian Agent-Based Models through Scene Activity AnalysisISPRS International Journal of Geo-Information, 4(3): 1627-1656. (pdf