Dijk, J. van (2007) Evaluating agent-based modelling as prediction tool for crime. Master's Thesis / Essay, Artificial Intelligence.
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Abstract
Crime forecasting is an instrument of growing importance for police enforcement around the globe. Police departments in the Netherlands have started first trials with forecasting techniques. Sentient Information Systems By, the company at which I conducted my research, provide crime analysis software for the police and were interested in alternative techniques to forecast crime. Because of this partnership, anonymous data on crime incidents and criminal individuals was available at Sentient for development purposes. Existing crime forecasting methods use data on crime incidents and related variables. This research studied the possibilities of the use of data on criminal individuals for the forecasting of crime. A natural choice for the modelling of crime on an individual level is the agent-based modelling (ABM) methodology. Previously developed crime ABM models have been investigated to find useful theories, techniques and ideas. Because the previous models were not meant for crime forecasting we used criminological literature to find additional ideas and techniques. This research gives an overview of an effort to use the ABM methodology to simulate crime based on data on individual criminals. The most important results are an overview of useful crime theories and techniques for the ABM methodology, a first-effort implementation of an ABM model to predict crime with individual data, a discussion of the limitations of this approach and suggestions for future work.
| Item Type: | Thesis (Master's Thesis / Essay) |
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| Degree programme: | Artificial Intelligence |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 15 Feb 2018 07:30 |
| Last Modified: | 15 Feb 2018 07:30 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/9082 |
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