The
Mastermind Project
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Overview
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Project
Goals
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Features
of Mastermind
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Current
Research
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Publications
Mastermind
is an interdisciplinary R&D; project in Computational Criminology jointly managed by the Software Technology Lab and the Institute for Canadian Urban Research Studies (ICURS) at Simon Fraser University. Mastermind is partly funded by the RCMP "E" Division, MITACS and NSERC.
Mastermind
is a computational framework for the modelling and simulation of criminal
behaviour in an urban environment. In other words, with Mastermind we run
criminal software agents through their daily routines in a simulated world.
However, Mastermind is not a single program: it is part of a framework for
developing computer programs that assist us in achieving our goals in
researching environmental criminology. To that end, we need to ensure that our
design is grounded in well-founded theory. It is also important that the
functionality of our programs focuses on enhancing and enabling research. Our
plan is to take advantage of the mathematical yet dynamic nature of software to
systematically integrate computational modelling and criminology theory. We hope
that valuable insight can be achieved through the use of computational
approaches to explore Criminology.
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To
construct computational models of criminology theory. In other words, we
want to transform our understanding of criminology phenomena into a model
that a computer can manipulate.
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To act
as a structure within which different criminology theories are precisely
defined and are able to interact, and allow us to learn from those
interactions.
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To
build a foundation that further software tools can be built upon.
Experimental tools allow researchers to test out new ideas in a
"sandbox" type of environment. Decision support tools use real-world
data to help stakeholders develop policy.
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Well-defined
formal structure: The underlying structure of Mastermind was developed using
the Abstract State Machine
(ASM) formalism. This has allowed us to implement Mastermind in a variety of
programming languages while maintaining the same core behaviour. It also
ensures that the underlying workings of the system are clear and easy to
understand, which helps when justifying any claims made on the basis of
experimental results.
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CoreASM
implementation: This version of Mastermind takes advantage of a close
connection to the underlying ASM structure. The simplicity of CoreASM
confers flexibility that allows for the rapid development of new types of
experiments, while at the same time providing expressive graphical output.
It is particularly well suited for analysis of the fundamental questions
posed by researchers.
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Java
implementation: This version of the program uses Geographic
Information System (GIS) data to generate a simulated environment that
mirrors an actual street network. The graphical user interface (GUI) allows
the user to zoom in on specific parts of the environment during execution,
or pan out for a general view. The computational power of Java allows for
large-scale experiments that involve multiple levels of real world data. We
have found this version very useful as a tool for demonstrating concepts in
environmental criminology.
With
a focus on environmental criminology, the topics we have been looking at in our
experiments include:
P. L. Brantingham, U. Glässer, P. Jackson, and M.
Vajihollahi. Collaborative Software Development for Criminology Research
Projects. Submitted to IEEE Software-Special Issue on Developing Scientific Software . Awaiting publication.
P. L. Brantingham, U. Glässer, P. Jackson, B.
Kinney, and M. Vajihollahi. A Computational Model for Simulating Spatial
and Temporal Aspects of Crime in Urban Environments. In Liu, L. and J.
Eck, eds., Artificial Crime Analysis Systems: Using Computer
Simulations and Geographic Information Systems. Information Science
Reference, 2008.
U. Glässer, P. Jackson, and M. Vajihollahi.
MasterMind: A Computational Framework for Studying Physical Crime. In:
Proceedings of the 14th
International Abstract State Machines Workshop (ASM'07).
Norway, June 7-9.
N. Pollard, M. Vajihollahi, G. Jenion. Utilizing
Advanced Tools in Criminology for Identification and Linkage of Auto
Thieves. In: Proceedings of the
33rd Annual Conference of the Western Society of
Criminology, Seattle, WA,
Feb 2006.
P. L. Brantingham, U. Glässer, B. Kinney, and M.
Vajihollahi. Simulation of Offender Travel in Urban Setting. In: Proceedings
of the 58th Annual Meeting of the American Society of Criminology,
Toronto, Canada, Jan 2006.
P. L. Brantingham, U. Glässer, B. Kinney, K.
Singh, and M. Vajihollahi. A Computational Model for Simulating Spatial
Aspects of Crime in Urban Environments. Systems, In: Proceedings of
2005 IEEE International Conference on Systems, Man and Cybernetics
(SMC'05), Vol. 4, Oct 2005, 3667-3674.
P. L. Brantingham, U. Glässer, B. Kinney, and M.
Vajihollahi. A Computational Model for Simulating Spatial and Temporal
Aspects of Crime in Urban Environments, In: 42nd Annual Meeting of the
Academy of Criminal Justice Sciences (ACJS'05), Chicago-USA, March
2005.
P. L. Brantingham, U. Glässer, B. Kinney, K.
Singh, and M. Vajihollahi. Modeling Urban Crime Patterns: Viewing
Multi-Agent Systems as Abstract State Machines. In D. Beauquier,
E. Börger and A. Slissenko (Eds.): Proc. 12th International Workshop
on Abstract State Machines.
Paris, France (2005) 101-118.
Computational Modeling and Simulation of Spatial
and Temporal Crime Pattern in Urban Environments. In
2006 Environmental Criminology and Crime Analysis conference (ECCA'06),
Chilliwack, BC, Canada, August 2006.
P. L. Brantingham, U. Glässer, K. Singh, and M.
Vajihollahi. A Computational Model for Simulating Spatial and Temporal
Aspects of Crime in Urban Environments. Technical Report
SFU-CMPT-TR-2005-10, Simon Fraser University, March 2005.
P. L. Brantingham, U. Glässer, K. Singh, and M.
Vajihollahi. Mastermind: Modeling and Simulation of Criminal Activity
in Urban Environments. Technical Report SFU-CMPT-TR-2005-01, Simon
Fraser University, February 2005.
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