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Dive into the research topics where Charlotte S. Vlek is active.

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Featured researches published by Charlotte S. Vlek.


international conference on artificial intelligence and law | 2013

Modeling crime scenarios in a Bayesian network

Charlotte S. Vlek; Henry Prakken; Silja Renooij; Bart Verheij

Legal cases involve reasoning with evidence and with the development of a software support tool in mind, a formal foundation for evidential reasoning is required. Three approaches to evidential reasoning have been prominent in the literature: argumentation, narrative and probabilistic reasoning. In this paper a combination of the latter two is proposed. In recent research on Bayesian networks applied to legal cases, a number of legal idioms have been developed as recurring structures in legal Bayesian networks. A Bayesian network quantifies how various variables in a case interact. In the narrative approach, scenarios provide a context for the evidence in a case. A method that integrates the quantitative, numerical techniques of Bayesian networks with the qualitative, holistic approach of scenarios is lacking. In this paper, a method is proposed for modeling several scenarios in a single Bayesian network. The method is tested by doing a case study. Two new idioms are introduced: the scenario idiom and the merged scenarios idiom. The resulting network is meant to assist a judge or jury, helping to maintain a good overview of the interactions between relevant variables in a case and preventing tunnel vision by comparing various scenarios.


Artificial Intelligence and Law | 2014

Building Bayesian networks for legal evidence with narratives: a case study evaluation

Charlotte S. Vlek; Hendrik Prakken; Silja Renooij; Bart Verheij

In a criminal trial, evidence is used to draw conclusions about what happened concerning a supposed crime. Traditionally, the three main approaches to modeling reasoning with evidence are argumentative, narrative and probabilistic approaches. Integrating these three approaches could arguably enhance the communication between an expert and a judge or jury. In previous work, techniques were proposed to represent narratives in a Bayesian network and to use narratives as a basis for systematizing the construction of a Bayesian network for a legal case. In this paper, these techniques are combined to form a design method for constructing a Bayesian network based on narratives. This design method is evaluated by means of an extensive case study concerning the notorious Dutch case of the Anjum murders.


Artificial Intelligence and Law | 2016

A method for explaining Bayesian networks for legal evidence with scenarios

Charlotte S. Vlek; Henry Prakken; Silja Renooij; Bart Verheij

In a criminal trial, a judge or jury needs to reason about what happened based on the available evidence, often including statistical evidence. While a probabilistic approach is suitable for analysing the statistical evidence, a judge or jury may be more inclined to use a narrative or argumentative approach when considering the case as a whole. In this paper we propose a combination of two approaches, combining Bayesian networks with scenarios. Whereas a Bayesian network is a popular tool for analysing parts of a case, constructing and understanding a network for an entire case is not straightforward. We propose an explanation method for understanding a Bayesian network in terms of scenarios. This method builds on a previously proposed construction method, which we slightly adapt with the use of scenario schemes for the purpose of explaining. The resulting structure is explained in terms of scenarios, scenario quality and evidential support. A probabilistic interpretation of scenario quality is provided using the concept of scenario schemes. Finally, the method is evaluated by means of a case study.


2014 Workshop on Computational Models of Narrative | 2013

Representing and Evaluating Legal Narratives with Subscenarios in a Bayesian Network

Charlotte S. Vlek; Henry Prakken; Silja Renooij; Bart Verheij

In legal cases, stories or scenarios can serve as the context for a crime when reasoning with evidence. In order to develop a scientifically founded technique for evidential reasoning, a method is required for the representation and evaluation of various scenarios in a case. In this paper the probabilistic technique of Bayesian networks is proposed as a method for modeling narrative, and it is shown how this can be used to capture a number of narrative properties. Bayesian networks quantify how the variables in a case interact. Recent research on Bayesian networks applied to legal cases includes the development of a list of legal idioms: recurring substructures in legal Bayesian networks. Scenarios are coherent presentations of a collection of states and events, and qualitative in nature. A method combining the quantitative, probabilistic approach with the narrative approach would strengthen the tools to represent and evaluate scenarios. In a previous paper, the development of a design method for modeling multiple scenarios in a Bayesian network was initiated. The design method includes two narrative idioms: the scenario idiom and the merged scenarios idiom. In this current paper, the method of Vlek, et al. (2013) is extended with a subscenario idiom and it is shown how the method can be used to represent characteristic features of narrative.


Law, Probability and Risk | 2016

Arguments, scenarios and probabilities: connections between three normative frameworks for evidential reasoning

Bart Verheij; Floris Bex; Sjoerd T. Timmer; Charlotte S. Vlek; John-Jules Ch. Meyer; Silja Renooij; Henry Prakken


international conference on artificial intelligence and law | 2015

Constructing and understanding Bayesian networks for legal evidence with scenario schemes

Charlotte S. Vlek; Henry Prakken; Silja Renooij; Bart Verheij


international conference on legal knowledge and information systems | 2014

Extracting scenarios from a Bayesian network as explanations for legal evidence

Charlotte S. Vlek; Hendrik Prakken; Silja Renooij; Bart Verheij


international conference on legal knowledge and information systems | 2015

Representing the quality of crime scenarios in a Bayesian network

Charlotte S. Vlek; Henry Prakken; Silja Renooij; Bart Verheij


international conference on legal knowledge and information systems | 2013

Unfolding crime scenarios with variations: a method for building a Bayesian network for legal narratives

Charlotte S. Vlek; Henry Prakken; Silja Renooij; Bart Verheij


Archive | 2016

When stories and numbers meet in court : Constructing and Explaining Bayesian Networks for Criminal Cases with Scenarios

Charlotte S. Vlek

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Bart Verheij

University of Groningen

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