Toward representing interpretation in factor-based models of precedent

Rigoni, Adam

doi:10.1007/s10506-023-09384-5

Artif Intell Law

2024

DOI: 10.1007/s10506-023-09384-5

|View full text |Cite

Toward representing interpretation in factor-based models of precedent

Adam Rigoni

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Intermediate factors and precedential constraint

Bench-Capon

2024

Artif Intell Law

View full text Add to dashboard Cite

This paper explores the extension of formal accounts of precedential constraint to make use of a factor hierarchy with intermediate factors. A problem arises, however, because constraints expressed in terms of intermediate factors may give different outcomes from those expressed only using base level factors. We argue that constraints that use only base level factors yield the correct outcomes, but that intermediate factors play an important role in the justification and explanation of those outcomes. The discussion is illustrated with a running example.

show abstract

Intermediate factors and precedential constraint

Bench-Capon

2024

Artif Intell Law

View full text Add to dashboard Cite

show abstract

Precedent-based reasoning with incomplete information for human-in-the-loop decision support

Odekerken,

Bex,

Prakken

2024

Artif Intell Law

View full text Add to dashboard Cite

We define and study the notions of stability and relevance for precedent-based reasoning, focusing on Horty’s result model of precedential constraint. According to this model, precedents constrain the possible outcomes for a focus case, which is a yet undecided case, where precedents and the focus case are compared on their characteristics (called dimensions). In this paper, we refer to the enforced outcome for the focus case as its justification status. In contrast to earlier work, we do not assume that all dimension values of the focus case or the precedent cases have been established with certainty: rather, each dimension is assigned a set of possible values. We define a focus case as stable if its justification status is the same for every choice of the possible values. For focus cases that are not stable, we study the task of identifying relevance: which possible values should be excluded to make the focus case stable? In addition, we introduce the notion of possibility to verify if a user can assign an outcome to an unstable focus case without making the case base of precedents inconsistent. We show how the tasks of identifying justification, stability, relevance and possibility can be applied for human-in-the-loop decision support. Finally, we discuss the computational complexity of these tasks and provide efficient algorithms.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Toward representing interpretation in factor-based models of precedent

Cited by 2 publications

References 30 publications

Intermediate factors and precedential constraint

Intermediate factors and precedential constraint

Precedent-based reasoning with incomplete information for human-in-the-loop decision support

Contact Info

Product

Resources

About