Agents - the 'atomic unit' of social systems? @AAG 2017

As part of the Symposium on Human Dynamics in Smart and Connected Communities at the forthcoming AAG Annual Meeting in Boston we have organized 2 sessions under the title of "Agents - the 'atomic unit' of social systems?" (session IDs 4169 & 4269). These will be held on on Saturday, 4/8/2017, from 8:00 am to 11.40 (we did not chose this time slot). Below you can see the session description and the list of speakers and titles. We hope some of the readers of this blog can make it to the sessions.

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.

This session will present 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. 

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.

4169 Symposium on Human Dynamics in Smart and Connected Communities: Agents - the 'atomic unit' of social systems? 1 

Saturday, 4/8/2017, from 8:00 AM - 9:40 AM in Regis, Marriott, Third Floor

Chair: Nick Malleson

Presentations:

• *Kurtis James Garbutt, Taku Fujiyama: and Claire Ellul
• Title: Agentising Vulnerability: Modelling the impact of NGO Response on Vulnerability during Flood events.
• *Zhu Jin and Sara Metcalf:
• Title: Developing Ontology for Agent-Based Modeling.
• *Frank Dignum and Virginia Dignum:
•  Title: Social Foundations for Agent Based Models.
• *Marcus Saraiva:
• Title: The AXS Model: An Agent-Based Simulation Approach for Accessibility and Centrality.
• Koen Haziel Van Dam:
•   Discussant: Visualizing Spatial Outputs from Agent-based Models

4269 Symposium on Human Dynamics in Smart and Connected Communities: Agents - the 'atomic unit' of social systems? 2 

Saturday, 4/8/2017, from 10:00 AM - 11:40 AM in Regis, Marriott, Third Floor

Chair: Alison Heppenstall 

Presentations:

• *Koen Haziel Van Dam and Chris M. Mazur:
• Title: Using household questionnaires to create realistic agents for energy system analysis.
• *Dawn C. Parker, Xiongbing Jin, Babin Robert, Xinyue Pi, Yu Huang, Pedram Fard and Jeff Casello: 
• Title: Modelling atomic housing market agents: Conceptual and data challenges.
• *Stephen Law and Yao Shen: 
• Title: House Price Spatial Diffusions on Street Networks.
• *Andrew Crooks, William G Kennedy, Annetta Burger, Talha Oz and  Alison Heppenstall:
• Title: Megacities Through The Lens of Computational Social Science.
• *Alison Heppenstall, Andrew Crooks and Nick Malleson:
• Title: The interplay of agent-based modelling and theory: Current practices and future trends.

We hope you will stay around and attend these sessions. See you in Boston.

Applications of Agent-based Models

Often I get asked the question along the lines of: "how are agent-based models are being used outside academia, especially in government and private industry?" So I thought it was about time I briefly write something about this.

Let me start with a question I ask my students when I first introduce agent-based modeling: "Have you ever seen an agent-based model before?" Often the answer is NO, but then I show them the following clip from MASSIVE (Multiple Agent Simulation System in Virtual Environment) where agent-based models are used in a variety of movies and TV shows. But apart from TV shows and movies where else have agent-based models been used?

There are two specific application domains where agent-based modeling has taken off. The first being pedestrian simulation for example, Legion,  Steps and EXODUS simulation platforms. The second is the area of traffic modeling for example, there are several microsimulation/agent-based model platforms such as PTV Visum, TransModeler and Paramics. Based on these companies websites they have clients in industry, government and academia.

If we move away from the areas discussed above, there is a lot of writing about the potential of agent-based modeling. For example, the Bank of England had a article entitled "Agent-based models: understanding the economy from the bottom up" which to quote from the summary:

"considers the strengths of agent-based modelling, which explains the behaviour of a system by simulating the behaviour of each individual ‘agent’ in it, and the ways that it can be used to help central banks understand the economy."

Similar articles can be seen in the New York Times and the Guardian to name but a few. But where else have agent-based models been used? A sample (and definitely not an exhaustive list) of applications and references are provided below for interested readers:

• Southwest Airlines used an agent-based model to improve how it handled cargo (Seibel and Thomas, 2000).
• Eli Lilly used an agent-based model for drug development (Bonabeau, 2003a).
• Pacific Gas and Electric: Used an agent based model to see how energy flows through the power grid (Bonabeau, 2003a).
• Procter and Gamble used an agent-based model to understand its consumer markets (North et al., 2010) while Hewlett-Packard used an agent-based model to understand how hiring strategies effect corporate culture (Bonabeau, 2003b).
• Macy’s have used agent-based models for store design (Bonabeau, 2003b).
• NASDAQ used and agent based model to explore changes to Stock Market's decimalization (Bonabeau, 2003b; Darley and Outkin, 2007).
• Using a agent-based model to explore capacity and demand in theme parks (Bonabeau, 2000).
• Traffic and pedestrian modeling (Helbing and Balietti, 2011).
• Disease dynamics (e.g. Eubank et al., 2004).
• Agent-based modeling has also been used for wild fire training, incident command and community outreach (Guerin and Carrera, 2010). For example SimTable was used in the  2016 Sand Fire in California. 
• InSTREAM: Explores how river salmon populations react to changes (Railsback and Harvey, 2002).

While not a comprehensive list, it is hoped that these examples and links will be useful if someone asks the question I started this post with. If anyone else knows of any other real world applications of agent-based modeling please let me know (preferably with a link to a paper or website).
 
References

• Bonabeau, E. (2000), 'Business Applications of Social Agent-Based Simulation', Advances in Complex Systems, 3(1-4): 451-461.
• Bonabeau, E. (2003a), 'Don’t Trust Your Gut', Harvard Business Review, 81(5): 116-123.
• Bonabeau, E. (2003b), 'Predicting the Unpredictable', Harvard Business Review, 80(3): 109-116.
• Darley, V. and Outkin, A.V. (2007), NASDAQ Market Simulation: Insights on a Major Market from the Science of Complex Adaptive Systems, World Scientific Publishing, River Edge, NJ.
• Eubank, S., Guclu, H., Kumar, A.V.S., Marathe, M.V., Srinivasan, A., Toroczkai, Z. and Wang, N. (2004), 'Modelling Disease Outbreaks in Realistic Urban Social Networks', Nature, 429: 180-184.
• Guerin, S. and Carrera, F. (2010), 'Sand on Fire: An Interactive Tangible 3D Platform for the Modeling and Management of Wildfires.' WIT Transactions on Ecology and the Environment, 137: 57-68.
• Helbing, D. and Balietti, S. (2011), How to do Agent-based Simulations in the Future: From Modeling Social Mechanisms to Emergent Phenomena and Interactive Systems Design, Santa Fe Institute, Working Paper 11-06-024, Santa Fe, NM.
• North, M.J., Macal, C.M., Aubin, J.S., Thimmapuram, P., Bragen, M., Hahn, J., J., K., Brigham, N., Lacy, M.E. and Hampton, D. (2010), 'Multiscale Agent-based Consumer Market Modeling', Complexity, 15(5): 37-47.
• Railsback, S.F. and Harvey, B.C. (2002), 'Analysis of Habitat Selection Rules using an Individual-based Model', Ecology, 83(7): 1817-1830.
• Seibel, F. and Thomas, C. (2000), 'Manifest Destiny: Adaptive Cargo Routing at Southwest Airlines', Perspectives on Business Innovation, 4: 27-33.