Friday, March 27, 2015

Bumble Bee Colonies

When reading papers about agent-based models / individual-based models, I am always curious if the model can be reproduced from the description in said paper. Specifically whether there is sufficient information in the paper to reproduce the model and the results. Often we task students with such a task as a learning exercise and I thought it would be nice to show you one such example done by Dale Brearcliffe.

The model that was reproduced is entitled "The Ontogeny of the Interaction Structure in Bumble Bee Colonies: A MIRROR Model" by Hogeweg and Hesper (1983) which explored whether or not an individual-oriented model of population dynamics and simple bumble bee behaviors could produce the ontogeny of the social interaction of the colony? The original model used MIRSYS, a program written   in INTERLISP. Dale was able to take the paper and reproduce the model using NetLogo, but not replicate the results (click here to read more and download the model).

Graphical User Interface of Reproduced  Model



Nest composition and development in the original model (Source: Hogeweg and Hesper, 1983).
Nest composition and development in the reproduced model.

Full Reference:
Hogeweg, P. and Hesper, B. (1983), 'The Ontogeny of the Interaction Structure in Bumble Bee Colonies: A MIRROR Model', Behavioral Ecology and Sociobiology, 12(4): 271-283. 

For those interested in reproduction and replication have a look at the following articles:
Axtell, R., Axelrod, R., Epstein, J.M. and Cohen, D. (1996), 'Aligning Simulation Models: A Case Study and Results', Computational and Mathematical Organization Theory, 1(2): 123-141. 
Drummond, C. (2009), 'Replicability is Not Reproducibility: Nor is it Good Science', Proceedings of the 4th Workshop on Evaluation Methods for Machine Learning at the 26th International Conference on Machine Learning, Montreal, Canada.
Wilensky, U. and Rand, W. (2007), 'Making Models Match: Replicating an Agent-Based Model', Journal of Artificial Societies and Social Simulation, 10(4): 2, Available at http://jasss.soc.surrey.ac.uk/10/4/2.html.
 

Thursday, March 26, 2015

Collective Behavior of In-group Favoritism

We just had a paper accepted in Advances in Complex Systems entitled "The Effect of In-group Favoritism on the Collective Behavior of Individuals' Opinions." In the paper we develop and an agent-based model to explore how individuals interact and how more  collective behaviors emerge (e.g. reaching a consensus or the spreading of opinions). The abstract of the paper is as follows:

Empirical findings from social psychology show that sometimes people show favoritism toward in-group members in order to reach a global consensus, even against individuals' own preferences (e.g., altruistically or deontically). Here we integrate ideas and findings on in-group favoritism, opinion dynamics, and radicalization using an agent-based model entitled cooperative bounded confidence (CBC). We investigate the interplay of homophily, rejection, and in-group cooperation drivers on the formation of opinion clusters and the emergence of extremist, radical opinions. Our model is the first to explicitly explore the effect of in-group favoritism on the macro-level, collective behavior of opinions. We compare our model against the two-dimentional bounded confidence model with rejection mechanism, proposed by Huet et al. (2008), and find that the number of opinion clusters and extremists is reduced in our model. Moreover, results show that group influence can never dominate homophilous and rejecting encounters in the process of opinion cluster formation. We conclude by discussing implications of our model for research on collective behavior of opinions emerging from individuals' interaction. 
 Keywords: Opinion dynamics; in-group favoritism; homophily; radicalization; extremism.


Full reference:
Alizadeh, M., Cioffi-Revilla, C. and Crooks, A.T. (2015), The Effect of In-group Favoritism on the Collective Behavior of Individuals' Opinions, Advances in Complex Systems. DOI: 10.1142/S0219525915500022 (pdf)
The code for the model is available from here.

Friday, March 20, 2015

Lipari School on Computational Social Science

If you are wondering what to do between July 26 and August 1, this summer, you might be interested in this years Lipari School on Computational Social Science which is focusing on Algorithms, Data, and Models for Social and Urban Systems

What will be taught at the summer school and why? To answer the these questions and to quote from the the homepage of the school:
 "Social and urban systems have been the focus of social science theory and research for centuries, but only until recently have computational approaches enabled novel explorations of challenging and enduring research questions and the opening of new frontiers for investigation. What is the role of Computational Social Science in advancing the science of social and urban systems? Which advanced algorithms and data structures play a key role in these investigations? In 2015 our Lipari Summer School in CSS will address questions such as the role of GIS (geographic/geospatial information systems), social media, big social data, agent-based models, network models, and their integration in the study, design, and implementation of social and urban systems. "
The speakers will be:
Special guest speakers will be:
To find out how to apply to attend the summer school click here. Students are encouraged to apply early because enrollment is competitive and limited.

Thursday, February 12, 2015

Village Model

http://village.anth.wsu.edu/node/67
What now seems like a very long long time ago, when I was getting up to speed with Agent-based modeling and GIS, I came across a great edited book entitled "Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes". 

One chapter in particular that I really enjoyed because of its clarity and use of data was by Kohler et al. (2000) entitled "Be There Then: A Modeling Approach to Settlement Determinants and Spatial Efficiency Among Late Ancestral Pueblo Populations of the Mesa Verde Region, U.S. Southwest". 

The chapter explored the question of why did Pueblo people vary their living arrangements between  compact villages and dispersed hamlets between 901-1287AD? To this day, I use this chapter when I am teaching about early agent-based models. While the initial model was implemented in Swarm, it has now been ported to Repast and developed further by an NSF supported program called Village Ecodynamics Project.




Full Reference:
Kohler, T.A., Kresl, J., Van Wes, Q., Carr, E. and Wilshusen, R.H. (2000), 'Be There Then: A Modeling Approach to Settlement Determinants and Spatial Efficiency Among Late Ancestral Pueblo Populations of the Mesa Verde Region, U.S. Southwest', in Kohler, T.A. and Gumerman, G.J. (eds.), Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes, Oxford University Press, Oxford, UK, pp. 145-178.

Monday, February 09, 2015

Geosimulation and Big Data: A Marriage made in Heaven or Hell? Schedule

Do you like big data and geosimulation and wondering when to book flights or which sessions to attend at the forthcoming AAG Annual Meeting,  If so, you might like our sessions entitled "Geosimulation and Big Data: A Marriage made in Heaven or Hell? " taking place on Wednesday the 22nd of April 2015.

Abstract of the Sessions:

In recent years, human emotions, intentions, moods and behaviors have been digitised to an extent previously unimagined in the social sciences. This has been in the main due to the rise of a vast array of new data, termed 'Big Data'.  These new forms of data have the potential to reshape the future directions of social science research, in particular the methods that scientists use to model and simulate spatially explicit social systems. Given the novelty of this potential "revolution" and the surprising lack of reliable behavioral insight to arise from Big Data research, it is an opportune time to assess the progress that has been made and consider the future directions of socio-spatial modelling in a world that is becoming increasingly well described by Big Data sources.

In these sessions we will have methodological, theoretical and empirical papers that that engage with any aspect of geospatial modelling and the use of Big Data. We are particularly interested in the ways that insight into individual or group behavior can be elucidated from new data sources - including social media contributions, volunteered geographical information, mobile telephone transactions, individually-sensed data, crowd-sourced information, etc. -  and used to improve models or simulations.  Topics include, but are not limited to:
  • Using Big Data to inform individual-based models of geographical systems;
  • Translating Big Data into agent rules;
  • Elucidating behavioral information from diverse data;
  • Improving simulated agent behavior;
  • Validating agent-based models (ABM) with Big Data;
  • Ethics of data collected en masse and their use in simulation.
2192 Geosimulation and Big Data: A Marriage made in Heaven or Hell? (1)

Wednesday, 4/22/2015.
8:00 AM - 9:40 AM.
600a Classroom, University of Chicago Gleacher Center, 6th Floor.

Chair: Nick Malleson 

Abstracts:

*Atsushi Nara:
A GPGPU approach for simulating and analyzing human dynamics
*Kira KowalskaJohn Shawe-Taylor and Paul Longley:
 Data-driven modelling of police patrol activity 
*Martin Zaltz Austwick, Gustavo Romanillos Arroyo and Borka Moya-Gomez:
Simulating Rush Hour Bicycle Traffic in Madrid 
*Hai Lan  and Paul Torrens:
Voxel based Cellular Automata with massive cells for Geo-simulation: Ice dynamics simulation in Antarctic locations as example
*Philippe J. Giabbanelli, Thomas Burgoine, Pablo Monsivais and James Woodcock:
Using big data to develop individual-centric models of food behaviours

2292 Geosimulation and Big Data: A Marriage made in Heaven or Hell? (2) 

Wednesday, 4/22/2015.
10:00 AM - 11:40 AM.
600a Classroom, University of Chicago Gleacher Center, 6th Floor.

Chair: Alison Heppenstall

Abstracts:

*Kostas Cheliotis:
Coupling Public Space Simulations with Real-Time Data Streams 
*Andrew Crooks and Sarah Wise:
Leveraging Crowdsourced data for Agent-based modeling: Opportunities, Examples and Challenges 
*Ed Manley, Chen Zhong and Michael Batty:
Towards Real-Time Simulation of Transportation Disruption - Building Agent Populations from Big Mobility Data 
*Alison Heppenstall, *Nick Malleson and Andrew Evans:
Evaluating Big Data demographics for population modelling 
Muhammad Adnan, Alistair Leak and *Paul Longley:
Exploring the geo-temporal patterns of Twitter messages

2492 Geosimulation and Big Data: A Marriage made in Heaven or Hell? (3) Discussion Session

Wednesday, 4/22/2015.
1:20 PM - 3:00 PM.
600a Classroom, University of Chicago Gleacher Center, 6th Floor.

Chair: Nick Malleson

Abstracts:
 
*Paul M Torrens and Hai Lan:
Micro big data and geosimulation 
*Mark Birkin:
The Ten Commandments of Big Data 
 2:00 PM to 3:00PM: Discussion

 Organizers

  • Alison Heppenstall, School of Geography, University of Leeds
  • Nick Malleson, School of Geography, University of Leeds
  • Andrew Crooks, Department of Computational Social Science, George Mason University
  • Paul Torrens, Department of Geographical Sciences, University of Maryland
  • Ed Manley, Centre for Advanced Spatial Analysis, University College London