Postdoctoral Research Fellow in Urban Simulation

The George Mason University, Department of Geography and Geoinformation Science (GGS), in the College of Science invites application for a Postdoctoral Research Fellow position beginning August 1st, 2019. The project, which is supported by the Defense Advanced Research Projects Agency (DARPA), is jointly conducted by Andreas Züfle, Dieter Pfoser, and Andrew Crooks at GMU, and by Carola Wenk at Tulane. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason’s academic and culturally inclusive environment.

Responsibilities: 

The primary job responsibilities of this position consist of the design, development and refinement of an agent-based simulation framework of urban areas. For this purpose, we are using the existing Multiagent Simulation Toolkit (MASON) platform (written in Java) that has been developed at GMU. Using MASON, new agent logic will have to be implemented, thus creating agents that use socially plausible rules to traverse their simulated world, and to interact with other agents. This project has started in Spring 2018, and such a simulation has already been developed. A main responsibility will be to implement more complex agent logic efficiently, thus allowing more agents to make more complex decisions, find shortest paths between locations, and interact with their simulated world, at the same time. For this purpose, implemented algorithms will need to be highly parallelizable, thus allowing to scale simulation via distribution among computing clusters located at GMU and Tulane. The successful candidate will also supervise graduate-level research assistants, collaborate with fellow scholars, and promote the department’s accomplishments through publications, presentations, and other public events.

Required Qualifications:

• Ph.D. in computer science, modeling and simulation, or closely related field;
• Experience with Agent-Based Modeling and social science simulation;
• Excellent written communication skills demonstrated by prior publications; and
• A track record that demonstrates the ability to work well with interdisciplinary research teams.

Preferred Qualifications:

• Strong programming skills in Java.

More Details: 

For more details and how to apply see: https://jobs.gmu.edu/postings/45722

Call for Papers: GeoSim 2019

The 2nd International Workshop on Geospatial Simulation (GeoSim) focuses on all aspects of simulation as a general paradigm to model and predict spatial systems and generate spatial data. New simulation methodologies and frameworks, not necessarily coming from the SIGSPATIAL community, are encouraged to participate. Example topics include, but are not limited to:

• Urban Simulation
• Agent Based Models for Spatial Simulation
• Multi-Agent Based Spatial Simulation
• Big Spatial Data Simulation
• Spatial Data/Trajectory Generators
• Road Traffic Simulation
• Environmental Simulation
• GIS using Spatial Simulation
• Interactive Spatial Simulation
• Spatial Simulation Parallelization and Distribution
• Geo-Social Simulation and Data Generators
• Social Unrest and Riot Prediction using Simulation
• Spatial Analysis based on Simulation
• Behavioral Simulation
• Verifying, and Validating Spatial Simulations
• Applications for Spatial Simulation

The workshop seeks high-quality full (8 pages) and short (4 pages) papers that will be peer-reviewed. Once accepted, at least one author is required to register for the workshop and the ACM SIGSPATIAL conference (which will be in Chicago, Illinois), as well as attend the workshop to present the accepted work which will then appear in the ACM Digital Library. 

This workshop should also be of interest to everyone who works with spatial data. The simulation methods that will be presented and discussed in the workshop should find a wide application across the community by producing benchmark datasets that can be parameterized and scaled. Simulated data sets will be made available to the community via the website.

More information about the workshop along with key dates is available at: https://www.geosim.org/  

Guest Editorial for Spatial Agent-based Models: Current Practices and Future Trends

Over the last few years we have seen spatial agent-based modeling beginning to bridge the gap from cautious early adoption towards general acceptance within the geographical sciences. One of the key features that has contributed to this is its ability to represent individual characteristics and behaviors.

In order to capture this evolution a while ago, Alison Heppenstall and myself  put out a call for papers that not only asked for papers that looked at current trends in agent-based modeling but also  for those  that highlighted and addressed the advances and challenges that researchers working within the area of spatial agent-based models face. We are happy to say this call is now over and in the current issue of GeoInformatica there are 6 great papers (full citations and links are provided below) and along with a editorial. The papers present not only a great synthesis of the current practices but also several of the key advances and challenges within the realm of spatial agent-based modeling are brought to bare. 

Several common themes will become apparent when reading the articles. All the authors were in agreement that while there has been a noticeable uptake in agent-based modeling, more work is needed to bridge the gap to acceptance as a standard tool within the spatial sciences (e.g. Polhill et al., 2019). Data (variable quality and availability) was an issue that was discussed by almost all of the authors, particularly how to translate high quality data into models to create behavioral rules and the use of novel forms of data to calibrate an empirical model (e.g. Crols and Malleson, 2019). How to represent and simulate behavior in agent-based models was also a recurrent issue with two papers discussing how approaches borrowed from machine learning can be used to improve the representation of behavior (e.g. Runck et al., 2019; Abdulkareem et al., 2019). How to create models that could scale from the micro to macro was another theme with the point being made that current agent-based modeling architectures do not foster models that are easily translatable to a regional or global context (e.g. Taillandier et al., 2019), nor are interactions across scales adequately addressed in most models (e.g. Lippe et al., 2019). The papers also highlight that to cross the bridge from novel tool to full acceptance as a standard tool within the geographical sciences, spatial agent-based modeling still has some way to go. However, the papers in this special issue can therefore be seen as a stepping stone towards this.

Papers in the Special Issue:

• Abdulkareem, S.H., Mustafa, Y.T., Augustijn, E.-W. and Filatova, T. (2019), 'Bayesian Networks for Spatial Learning: A Workflow on Using Limited Survey Data for Intelligent Learning in Spatial Agent-based Models', Geoinformatica, 23(2): 243-268. 
• Crols, T. and Malleson, N. (2019), 'Quantifying the Ambient Population using Hourly Population Footfall Data and an Agent-Based Model of Daily Mobility', Geoinformatica, 23(2): 201-220.
• Lippe, M., Bithell, M., Gotts, N., Natalini, D., Barbrook-Johnson, P., Giupponi, C., Hallier, M., Hofstede, G.J., Le Page, C., Matthews, R.B.,  Schlüter, M., Smith, P., Teglio, A. and Thellmann, K. (2019), 'Using Agent-based Modelling to Simulate Social-ecological Systems Across Scales', GeoInformatica, 23(2): 269-298.
• Polhill, J.G., Ge, J., Hare, M.P., Matthews, K.B., Gimona, A., Salt, D. and Yeluripati, J. (2019), 'Crossing the Chasm: A ‘Tube-map’for Agent-based Social Simulation of Policy Scenarios in Spatially-distributed Systems', GeoInformatica, 23(2): 169-199.
• Runck, B.C., Manson, S., Shook, E., Gini, M. and Jordan, N.R. (2019), 'Using Word Embeddings to Generate Data-driven Human Agent Decision-making from Natural Language', Geoinformatica, 23(2): 243-268.
• Taillandier, P., Gaudou, B., Grignard, A., Huynh, Q.N., Marilleau, N., Caillou, P., Philippon, D. and Drogoul, A. (2019), 'Building, Composing and Experimenting Complex Spatial Models with the GAMA Platform', GeoInformatica, 23(2): 299-322.

Our Editorial:

Heppenstall, A. and Crooks, A.T. (2019), Guest Editorial for Spatial Agent-based Models: Current Practices and Future Trends, GeoInfomatica. 23(2): 243-268 (pdf)