New RA Job at UCL: “Agent-based simulation of crime and citizens with proactive policing”

Just came across this new job at UCL which might be relevant to people interested in agent-based modelling and crime simulation.
https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5041178&ownertype=fair&jcode=1340447

"Applicants are invited for a Research Associate position based at the UCL Department of Civil, Environmental and Geomatic Engineering (CEGE). The successful applicant will work as part of a team on an exciting multi-disciplinary project – examining Crime, Policing and Citizens (CPC) and their interaction in space-time networks. The successful candidate will create and maintain a Greater London wide database of police activities, classified by location, and relate these to (policing relevant) citizen characteristics and activities.

The post is available from 1st October and is funded for 2.5 years in the first instance."

 

Crime Simulation and Genetic Algorithms

I recently presented a paper at the GISrUK conference about using a genetic algorithm to calibrate a model and to better understand the behaviour of simulated burglars.

Slides are available here: GISrUK 2013 Presentation and the abstract is here: GISrUK 2013 Abstract.

The aim of the work is to use an artificial intelligence algorithm to calibrate the behaviour of virtual burglars, bringing model results more in line with observed burglary patterns. As well as improving the accuracy of the model, the process might tell us something about the underlying human behaviour. The model is built on the ideas of Routine Activity Theory, the Rational Choice Perspective and the Geometric Theory of Crime. If the genetic algorithm finds that certain types of agent behaviour do not help to improve the accuracy of the burglary model, then this might tell us something about the applicability of the theories to the real world.

Crime Simulation with SimCity

The new SimCity game is causing quite a stir among the agent-based modelling community. Its simulation engine (called GlassBox) is basically an agent-based model which allows individual sims to behave independently and build up to larger city-wide patterns (such as pollution, population happiness, traffic, etc.) This has already been used to model new road designs in Manchester (see this post).

Importantly, the game includes an add on called "Heroes and Villians" which  could have a use in crime simulation. It seems to focus mostly on comic book style crime fighters and mob bosses, but might have the potential to simulate some interesting crime patterns. Given the success in simulating traffic, this might well be a useful tool. It will be interesting to see how it pans out and whether or not it can be used for more than just playing games.  

For anyone interested, the developers of the game have also released a video showing how the simulation engine works. It's an excellent example of an agent-based model.

(Thanks to Andrew Crooks and Ed Manly for pointing me to SimCity and the Manchester work).

New Simulation Paper in CRIMINOLOGY

Daniel Birks, Michael Townsley and Anna Stewart have just published the first (?) agent-based simulation paper in the renowned CRIMINOLOGY journal entitled "Generative Explanations of Crime: Using Simulation to Test Criminological Theory". The paper is a brilliant example of a simple agent-based model which is able to test how three key theories in Environmental Criminology influence patterns of burglary.

The abstract is

This study demonstrates that computational modeling and, in particular, agent-based modeling (ABM) offers a viable compatriot to traditional experimental methodologies for criminology scholars. ABM can be used as a means to operationalize and test hypothetical mechanisms that offer a potential explanation for commonly observed criminological phenomena. This study tests whether the hypothesized mechanisms of environmental criminology are sufficient to produce several commonly observed characteristics of crime. We present an ABM of residential burglary, simulating a world inhabited by potential targets and offenders who behave according to the theoretical propositions of environmental criminology. A series of simulated experiments examining the impact of these mechanisms on patterns of offending are performed. The outputs of these simulations then are compared with several well-established findings derived from empirical studies of residential burglary, including the spatial concentration of crime, repeat victimization, and the journey to crime curve. The results from this research demonstrate that the propositions of the routine activity approach, rational choice perspective, and crime pattern theory provide a viable generative explanation for several independent characteristics of crime.

FutureICT Crime Exploratory

As part of a much larger European funding initiative, the FutureICT project is proposing to use ICT, Complexity Science and the Social Sciences to understand and manage complex, global, socially interactive systems, with a focus on sustainability and resilience. One project in particular, the Crime Exploratory, is highly relevant as it aimed to set up a pan-European crime modelling and data mining observatory, under the EU Collaborative projects and Coordination and Support Actions (CPCSA) funding stream.

Andy Evans recently attended the first CrimeExploratory meeting in Rome to present our work, and got to hear a series of interesting talks from crime modellers from across Europe, including discussions of the financial systems of organised crime, datamining of human trafficking data, and the tricky problem of modelling morality. The talks should be available on the project website soon.

New research website

I've just made a new website for my research: http://nickmalleson.co.uk/

I will continue to update this blog with crime simulation information though as soon as the project starts up again (shouldn't be long..). In the meantime I have been re-building the simulation from the ground up (e.g. the RepastCity project is a highly simplified version used for teaching urban modelling)

Call for Papers: 1st International Workshop on Advances in Computational Social Science

The workshop is in conjunction with 12th International Conference on Computational Science, June 4–6, 2012, Omaha, Nebraska, USA

Advances in computational systems and methods (parallel, distributed, cloud; agents, networks) are revolutionizing how social science research is done. It is now possible to simulate entire cities, for example, in tremendous detail, not only in terms of technical infrastructures like traffic, but also in terms of the social choices of individuals and how these interact with each other to produce complex phenomena. At the same time, advances in informatics infrastructures mean that more data and more detailed data are collected. These data are not just on our physical environment, but are also along social dimensions. The confluence of these two developments open up many possibilities, and social scientists are now probing questions that they could never ask before. Frequently, asking these questions generate even more inquiry into the interfaces between social science, computer science, information science, and engineering.

In this workshop, we aim to provide a forum for computational social scientists to share advances made in their respective fields, and the innovations they have developed across disciplinary boundaries: on models, methods, data integration and analysis, as well as interpretation of diverse social phenomena. We also hope to foster an environment for earnest dialogue between social scientists keen to employ sophisticated computational models and methods in their research, and computer/information scientists and engineers interested in understanding social science problems.
We invite original research papers on the following topics:

• Modeling methodologies
• Simulation strategies and algorithms
• Organization of heterogeneous social data
• Data-mining and machine learning on social, behavioral, and economic data
• Integration of social data into simulations
• Computational studies of specific social science problems

Computational social science papers that are relevant to this workshop, but cannot be easily classified based on the topics above will also be considered.

For more information, please see the workshop website.

Research completed!

I have recently completed my burglary simulation PhD and a copy of the thesis will be made available on my University of Leeds home page. There are lots of papers forthcoming which discuss the results and the implications for crime simulation and environmental criminology, I'll post them as they work their way through the reviewing process. The model itself is also going to be made available, and I'm hoping to make it more usable for other researchers and policy makers over the next few months.

In the thesis, I ran a scenario in Leeds, UK, that tried to predict the effects of a major urban development scheme on individual household burglary risk. The model simulated the daily movements "potential burglars" and the resulting crime patterns before and after the regeneration. Interestingly, the model predicted that a few houses in particular will face a disproportionately high risk as a result of the regeneration, due to the changing behaviour of the simulated burglars. The image below shows which houses might receive more (red) and fewer (green) burglaries once the urban development has finished. I am going to speak to policy-makers in Leeds about this in the coming weeks to see what they think about the results and whether or not some policy changes might come out of the research.




















And finally a quick plug to finish this post. I recently had a paper published in the journal "Computers, Environment and Urban Systems" which illustrates a working example of the prototype burglary simulation, based on an abstract city and the research was also mentioned in an article in The Guardian newspaper.

Testing Transport Routes and Burglary

I have recently run some tests with transport routes in my burglary simulation and have some nice results. The image shows what happens when a simulated burglar has to walk around (left) and when they're given a access to public transport (right). These are purely hypothetical simulations, but it shows some of the potential of the model.
















When the agent has to walk between their friend's house, drug dealer and their home, they are able to explore more of the city on the way. This gives them a much greater knowledge of the area when they need to commit a burglary.

When they use public transport to travel, on the other hand, they do not explore the surrounding area as they would do if they were walking. Therefore the burglaries are much more clustered around their anchor points (home address, friend's house and drug dealer).

Although this is a simple result I'm hoping that this type of experiment will be very useful when trying to predict real burglary rates.

New paper: Prototype Burglary Simulations For Crime Reduction and Forecasting

I have recently had a paper jointly authored with Patricia L. Brantingham, published in the journal Crime Patterns and Analysis, available online.

The journal introduces prototype version of the burglary simulation model and also illustrates some preliminary burglary predictions in an area of Leeds, UK. As the image below demonstrates, the early results are promising; the model is able to relatively accurately recreate crime patterns found in the real data.

Scientific Computing World Article

Felix Grant has just published an interesting article in Scientific Computing World about how statistical approaches have been applied to the social sciences (crime in particular) and how agent-based modelling is being used. He also does a short case-study on my PhD research.

If you're interested you can read the article on the scientific computing world website or on Felix's blog.

Crime Mapping Conference Presentation

I recently presented a paper entitled "Using Simulation to Predict Prospective Burglary Rates in Leeds and Vancouver" at the 7th National Crime Mapping Conference, 7th-8th May 2009 in Manchester, UK. The conference was a great success as usual, bringing together people from all areas of the police, community safety and academia.

The presentation briefly outlined the burglary simulation and showed some initial results. Here is the abstract and slides.

The following image is an extract of the burglary hotspots which were produced by the Vancouver Sky Train scenario. In this scenario I was experimenting with adding and removing Sky Train lines (a high-speed urban rail link) from Vancouver, Canada. When the simulation has been configured correctly we would like to predict what effect the new Canada Line (which is being build to support the 2010 winder Olympics) willl have on burglary rates in the city.

Simulation case studies in Vancouver

In January - February this year I was able to visit the Institute for Canadian Urban Research Studies (ICURS) at Simon Fraser University in Vancouver, BC, to work with expert criminologists Pat and Paul Brantingham. I was able to run a prototype of my simulation on Vancouver to see how crime rates might change if a new rapid-transit rail line was built.

There is a short presentation which has lots of information about how I used the Vancouver data to configure the model and the results of the case studies themselves. As an example, the following figure illustrates how space syntax analysis can be used to estimate how busy a road might be and therefore how easy it would be for a burglar agent to gain access to a property without being seen by passers-by.

Simulating Burglary - Working Paper

I have just finished a working paper entitled "Simulating Burglary with an Agent-Based Model", available here. It reports some results of my initial burglary prototype. This model uses relatively simple burglar agents and a grid-based virtual environment but is a good introduction to the more complex model that I'm developing for my PhD.

The following video shows an early prototype in action. The burglar agents are yellow and other people (home owners) are blue. Initially some of the burglars go to work in the green area, but often employment doesn't provide them with enough money and they choose to burgle instead. This is a vast simplification of real behaviour and will be improved in later developments, but works well as a proof-of-concept prototype.

Moving agents around a city - followup

Following on from a previous post about how to move agents around a road network using Repast Simphony, I have just finished developing a prototype version which others can download. The program loads a small hypothetical town with a few simple agents, some houses and some roads. The agents choose a random house and then travel there.




The code and some description about how it works are here. I hope it will be useful for others who are developing agent-based models or crime simulations in particular.

Artificial Crime Analysis Systems book

I have recently come across this new book, edited by Lin Lui and John Eck: Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems.

It is a collection of papers by the authors of new agent-based crime models as well as discussions surrounding other issues with crime simulation (such as validation, verification etc). This book is long overdue and very relevant, I recommend it as the first place to look for anyone interested in crime simulation.

Presentation at the British Society of Criminology conference

I have just given a presentation entitled "Improving burglary-reduction initiatives through a realistic agent-based model." at one of the "Geographies of Crime" sessions, organised by Professor Alex Hirschfield at the University of Huddersfield.

The abstract and slides are on my School of Geography webpage.

Presentation: Realistic Crime Simulation.

I recently attended a workshop at the National Centre for e-Social Science Fourth International Conference and gave a short presentation entitled "Realistic Crime Simulation: Predicting crime rates through a sound model of offender behaviour coupled with an accurate virtual environment" (it can be downloaded from my School of Geography webpage). The abstract is as follows:

Understanding the relationship between crime and the environment is an important research area in criminology. However, human systems are highly complex and influenced by a huge number of individual components, complex spatio-temporal interactions and human decisions which are at best complex and at worst seemingly irrational. As with other human systems, the complexity of the crime system, therefore, makes it extremely difficult to understand and predict crime patterns and to generate effective crime reduction policies.

To credibly model crime it is essential to be able to model the complex, dynamic interactions of the individuals and their environment which constitute a crime event. However, most studies to date suffer from an inability to model these micro-level interactions. Agent-based modelling is a methodology which works from the “bottom-up” and is able to capture emergent phenomena such as city-wide crime patterns which are built up from a multitude of individual crime occurrences. Such techniques are becoming very popular in the fields of urban studies in geography, but are still rarely used in criminology or by policy makers.

This paper will present an advanced agent-based model which couples a realistic framework for modelling offender behaviour with an accurate GIS virtual environment using the Repast Simphony toolset. We will use the model to evaluate and predict the success of genuine crime reduction scenarios implemented in the city of Leeds.

Visualising Agent Movements with GeoTime

I've recently started using GeoTime (r), produced by Oculus who were kind enough to kind enough to provide a student license. I think the software is intended for the police but it works very well for visualising any type of movement in a space. It's particularly good for analysing the movements of agents. It provides plug-ins for Excel and ArcGIS so it's easy to send model results to GeoTime and then visualise them.

These screen shots* show a burglar agent who is searching for a potential victim. The horizontal axis is used to show movement in space and the vertical axis shows movement over time. You can use Arc to project a map on the spatial plane. The bar at the bottom of the screen allows you to restrict the events to a particular temporal range and it can be dragged to show how movements vary dynamically (will try to make a video of this).






The software is particularly useful for debugging and validation. You can look at the behaviour of the agents very carefully and see if they are behaving as they should. For example, the agent above walked up and down the same street about 10 times. This is probably not accurate and shows that work is needed on the behaviour of the agents to bring it in to line with criminology theory.

You can also use the software to visualise multiple agents. This will be particularly useful when agents can interact because it is easy to see where groups of agents cluster spatially and temporally.



*GeoTime® software used courtesy of Oculus Info Inc. All GeoTime rights reserved.

Repast Simphony "no-GUI" Tutorial

UPDATE (7th March 2013): The link below doesn't work any longer but as the new Repast tutorials have been improved I don't intend to update it. Have a look at the Repast homepage.

I've been using Repast Simphony to build my agent-based crime model. Repast is a tool kit which has lots of really useful functions for organising agents, creating displays, scheduling events, working with GIS data, drawing charts, outputting data etc. Although Simphony is excellent I think there's quite a steep learning curve so I've written a short (1 hour) tutorial which will hopefully help to get people started:

http://portal.ncess.ac.uk/access/wiki/site/mass/simphony%20tutorial.html

Simphony now has a GUI which you can use to build models (the main tutorial goes through how to use this) but I've avoided this, preferring to program models directly.