Testimony, Credibility, and Explanatory Coherence

Thagard, Paul

doi:10.1007/s10670-005-4004-2

Cited by 37 publications

(28 citation statements)

References 20 publications

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“…With regards to the story-based approach, Verheij (2000) compares the Anchored Narratives Theory to formal logics for argumentation, Keppens and colleagues (e.g. Keppens and Schäfer 2006) and Josephson (2002) provide logical, model-based approaches to reasoning with crime scenarios and Thagard (2004Thagard ( , 2005 model stories and evidence in connectionist "coherence networks". A central theme in both the argument-based and the story-based theories is the structuring and analysis of one's reasoning so as to make sense of the case.…”

Section: Introductionmentioning

confidence: 99%

A hybrid formal theory of arguments, stories and criminal evidence

et al. 2010

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This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished, one argument-based and one storybased. In an argument-based approach to reasoning with evidence, the reasons for and against the occurrence of an event, e.g., based on witness testimony, are central. In a story-based approach, evidence is evaluated and interpreted from the perspective of the factual stories as they may have occurred in a case, e.g., as they are defended by the prosecution. In this paper, we argue that both arguments and narratives are relevant and useful in the reasoning with and interpretation of evidence. Therefore a hybrid approach is proposed and formally developed, doing justice to both the argumentbased and the narrative-based perspective. By the formalization of the theory and the associated graphical representations, our proposal is the basis for the design of software developed as a tool to make sense of the evidence in complex cases.

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Section: Introductionmentioning

confidence: 99%

A hybrid formal theory of arguments, stories and criminal evidence

et al. 2010

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“…The simplest way is choosing a subset-minimal explanation that explains all the observations. Thagard [18] computes the activation of the individual propositions: (causal) coherence between two units functions as an excitatory link between the units. Acceptance or rejection of an explanation is represented by the degree of activation of the individual propositions in the explanation.…”

Section: Figure 3: Two Explanationsmentioning

confidence: 99%

“…Thagard [18] has applied his connectionist model of abductive inference to the best explanation to legal cases, claiming that it provides a computational account of the story approach to legal evidence. Keppens and Schafer [9] have applied model-based reasoning with scenarios to automated support for the investigation of murder cases.…”

Section: Introductionmentioning

confidence: 99%

Formalising argumentative story-based analysis of evidence

Bex

Prakken

Verheij

2007

Proceedings of the 11th International Conference on Artificial Intelligence and Law

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In the present paper, we provide a formalised version of a merged argumentative and story-based approach towards the analysis of evidence. As an application, we are able to show how our approach sheds new light on inference to the best explanation with case evidence. More specifically, it will be clarified how the events in a case story that are considered to be proven abductively explain the otherwise unproven events of the case story. We compare our approach with existing AI work on modelling legal reasoning with evidence.

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“…Thagard [29] speaks in this connection of a "dual pathway model" of reasoning with testimonial evidence. He distinguishes a "default pathway" in which people almost automatically accept a testimony and a "reflective pathway" in which people build a model of the relevant knowledge and decide whether to believe the testimony by inference to the best explanation (IBE).…”

Section: Our Approachmentioning

confidence: 99%

Sense-making software for crime investigation: how to combine stories and arguments?

Bex¹,

Braak²,

Oostendorp³

et al. 2007

Law, Probability and Risk

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Sense-making software for crime investigation should be based on a model of reasoning about evidence that is both natural and rationally well-founded. A formal model is proposed that combines AI formalisms for abductive inference to the best explanation and for defeasible argumentation. Stories about what might have happened in a case are represented as causal networks and possible hypotheses can be inferred by abductive reasoning. Links between stories and the available evidence are expressed with evidential generalisations that express how observations can be inferred from evidential sources with defeasible argumentation. It is argued that this approach unifies two well-known accounts of reasoning about evidence, namely, anchored narratives theory and new evidence theory. After the reasoning model is defined, a design is presented for sense-making software that allows crime investigators to visualise their thinking about a case in terms of the reasoning model.

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Testimony, Credibility, and Explanatory Coherence

Cited by 37 publications

References 20 publications

A hybrid formal theory of arguments, stories and criminal evidence

A hybrid formal theory of arguments, stories and criminal evidence

Formalising argumentative story-based analysis of evidence

Sense-making software for crime investigation: how to combine stories and arguments?

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