On the Proof Dynamics of Inference to the Best Explanation

Josephson, John R.

doi:10.1007/978-3-7908-1792-8_15

Cited by 33 publications

(50 citation statements)

References 6 publications

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“…In the final example, Thagard (1989) found greater support for Peyer's guilt rather than innocence. Consistent with a more recent assessment of the same example (Josephson, 2001), we find more support for Peyer's innocence than guilt (not entirely contradicting the jury verdict). However, when the inference rules are applied, we find that both guilty and innocent propositions receive positive activation levels resulting in a hung verdict for the arguments (thus more consistent with the jury's findings in the first trial).…”

Section: Argument Structure and Connectionismsupporting

confidence: 88%

Addressing the homeland security problem: A collaborative decision‐making framework

Raghu¹,

Ramesh²,

Whinston³

2005

J. Am. Soc. Inf. Sci.

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A majority of critical decisions requires collaborative efforts among analysts to build situation awareness. Teams of decision makers frequently have to react to incoming facts and developing events in a timely fashion such that the consequences of the decisions made largely have a positive impact on a developing situation. This problem is further exacerbated due to the multitude of agencies involved in the decision-making process. Thus, the decision-making processes faced by the intelligence agencies are characterized by group deliberations that are highly ill structured and yield limited analytical tractability. In this context, a collaborative approach to providing cognitive support to decision makers using a connectionist modeling approach is proposed. The connectionist modeling of such decision scenarios offers several unique and significant advantages in developing systems to support collaborative discussions. Several inference rules for augmenting the argument network and to capture implicit notions in arguments are proposed. We further explore the effects of incorporating notions of information source reliability within arguments and the effects thereof.

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Section: Argument Structure and Connectionismsupporting

confidence: 88%

Addressing the homeland security problem: A collaborative decision‐making framework

Raghu¹,

Ramesh²,

Whinston³

2005

J. Am. Soc. Inf. Sci.

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“…Room for doubt is accounted for since an as yet unknown story might be the true one or since new evidence might make another of the known stories the best one. Both [90] and [165] sketch how this approach can be computationally modelled as inference to the best explanation. Like in Bayesian approaches, the direction of reasoning is from the hypotheses to the evidence (and then from the evidence to the hypotheses), since various hypotheses, respectively, scenarios are compared on how well they explain the available evidence.…”

Section: Story-based Approachesmentioning

confidence: 99%

Law and logic: A review from an argumentation perspective

Prakken

Sartor

2015

Artificial Intelligence

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This article reviews legal applications of logic, with a particularly marked concern for logical models of legal argument. We argue that the law is a rich test bed and important application field for logic-based AI research. First applications of logic to the representation of legal regulations are reviewed, where the main emphasis is on representation and where the legal conclusions follow from that representation as a matter of deduction. This includes the representation of deontic concepts, normative positions, legal ontologies, time and change. Then legal applications of logic are reviewed where legal rules are not just applied but are the object of reasoning and discourse. This includes arguing about applying statutory rules in unforeseen circumstances, interpretative reasoning in light of the facts of a case, and evidential reasoning to establish the facts of a case. This part of the review has special emphasis on argumentation-based approaches. This also holds for the final part, which discusses formal models of legal procedure and of multi-agent interaction in legal proceedings. The review concludes with identifying some of the main open research problems. The review shows that modern legal applications of logic confirm the recent trend of widening the scope of logic from deduction to information flow, argumentation and interaction.

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“…[13,17,11]). Logics for defeasible argumentation and other nonmonotonic logics, which only model modus-ponens-style reasoning, are less popular, presumably since they require the use of evidential generalisations, which arguably is cognitively less natural [14].…”

Section: Current Approaches In Aimentioning

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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On the Proof Dynamics of Inference to the Best Explanation

Cited by 33 publications

References 6 publications

Addressing the homeland security problem: A collaborative decision‐making framework

Addressing the homeland security problem: A collaborative decision‐making framework

Law and logic: A review from an argumentation perspective

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

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