How you can tell if the simulations in computational criminology are any good

Berk, Richard A.

doi:10.1007/s11292-008-9053-5

Cited by 35 publications

(39 citation statements)

References 53 publications

(43 reference statements)

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“…There are several questions regarding the validity of the simulated model and its implications for criminological theories. Three criteria for 'validating' computer models have been proposed [38]. The qualitative credibility is established if the model is consistent with what is expected of the result.…”

Section: Discussionmentioning

confidence: 99%

“…The internal quantitative credibility is met when the model output corresponds to observations that are a part of the data used to develop and calibrate the model. Furthermore, external quantitative credibility corresponds to the situation when the model output corresponds well to observations from data not used to develop and calibrate the model [38]. It needs to be kept in mind that in social sciences good and even valid evaluation data is difficult to obtain.…”

Section: Discussionmentioning

confidence: 99%

“…Agent based models do not represent an empirical test of the theory but rather the extent to which the theory is plausible [7]. Thus, validation of the model has to be accepted largely on the basis of qualitative credibility [38].…”

Section: Discussionmentioning

confidence: 99%

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Validating distance decay through agent based modeling

Verma

Marru

2013

Secur Inform

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The objectives of this research are to display the utility of using agent based model and simulated experiments in understanding criminal behavior. In particular, this research focuses upon the distance decay function that has wide applicability in understanding ways in which offenders move about their awareness space and select their targets for committing crime. The basis for distance decay is an assumption that the offender apprehends recognition by his neighbors and so tends to commit his crime a little away but not too far from his home location. But this is an untested assumption and based upon another assumption that recognition comes from frequent interactions. There is no simple way to test these assumptions in real life. This paper argues that simulated experiments using agent based modeling are appropriate methods for difficult to test criminological concepts. In this research, two types of agents are created-one representing the offender and the other-the victim. They are assigned specific characteristics that control their action such as moving in a neighborhood, making rational choice to maximize their gain while minimizing the risk of apprehension from interaction with other residents of the neighborhood. The simulation result displays that beginning with these small principles the final model emerges as a pattern of target selection similar to the distance decay function. The importance of this technique lies in the fact that such experiments provide the means to apply agent based modeling to validate a variety of criminological concepts. While the technique has limitations of validation it can help in understanding the behavior of offenders as they commit their crimes individually as well as in groups.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Validating distance decay through agent based modeling

Verma

Marru

2013

Secur Inform

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“…Highly specified models can be validated by comparing model output to aggregate statistics, and individual agent behavior to observed behaviors in a comparable population (Bruch and Atwell 2013; for a summary of empirical validation approaches, see Berk 2008). On the other hand, abstract models can be compared to observed patterns (Grimm et al 2005) or to hypothesized empirical relationships, which are based on observed mechanisms (Bruch and Atwell 2013).…”

Section: Simulation Challenges and Opportunitiesmentioning

confidence: 99%

Integrating Research Tools to Support the Management of Social-Ecological Systems Under Climate Change

Miller¹,

Morisette²

2014

E&S

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ABSTRACT. Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide datadriven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

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“…Berk (2008) examines the complexities of model validation, specifically degrees of credibility, for computational models and further concludes that simulation models can benefit the development and refinement of theory. However, criminologists must continue to test computer models against data [13]. Further, Townsley and Birks (2008) discuss the need for replication of computational model to enhance their validity [14].…”

Section: Introductionmentioning

confidence: 99%

Through a computational lens: using dual computer-criminology degree programs to advance the study of criminology and criminal justice practice

et al. 2013

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Computational criminology seeks to address criminological and criminal justice problems through the use of applied mathematics, computer science, and criminology. The development of mathematical and computational methods along with the emergence of cyberspace demonstrates the need for innovative degree programs that focus on computational criminology. The purpose of this article is to highlight the significance of dual computer-criminology degree programs. The article first discuses two major shifts in the study of criminology: the facilitation of new methodologies and data techniques; and, the development of new types of crime and delinquency through advancements in computer technology. Next, the article describes the need for dual computer-criminology degree programs and employs Florida State University's program as an example of what these programs offer aspiring criminologists. Finally, the article concludes with discussion of future plans for the Florida State University dual computer-criminology degree program that are applicable to other criminology programs both within the United States and also internationally.

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How you can tell if the simulations in computational criminology are any good

Cited by 35 publications

References 53 publications

Validating distance decay through agent based modeling

Validating distance decay through agent based modeling

Integrating Research Tools to Support the Management of Social-Ecological Systems Under Climate Change

Through a computational lens: using dual computer-criminology degree programs to advance the study of criminology and criminal justice practice

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