Paper Info
Title
Salvaging The Spirit Of The Meter-Models Tradition: A Model Of Belief Revision By Way Of An Abstract Idealization Of Response To Incoming Evidence Delivery During The Construction Of Proof In Court
Abstract
Inside the Juror (Hastie 1994) was, in a sense, a point of arrival for research developing formalisms that describe judicial decision making. Meter-based models of various kinds were mature, and even ready for giving way to such models that would concern themselves with the narrative content of the cases at hand, that a court is called to decide upon. Moreover, excessive emphasis was placed on lay factfinders, i.e. on jurors. It is noticeable that as "AI & Law" has become increasingly concerned with evidence in recent years - with efforts coordinated by Nissan & Martino, Zeleznikow, and others - the baggage of the meter-based models from jury research does not appear to be exploited. In this article, we try to combine their tradition with a technique of belief revision from artificial intelligence, in an attempt to provide an architectural component that would be complementary to models that apply representations or reasoning to legal narrative content.
Year
DOI
Venue
2004
10.1080/08839510490279889
APPLIED ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
belief revision,artificial intelligent
Computer science,Idealization,Narrative,Jury,Metre (music),Artificial intelligence,Judicial opinion,Epistemology,Rotation formalisms in three dimensions,Machine learning,Belief revision
Journal
Volume
Issue
ISSN
18.0
3-4
0883-9514
Citations 
PageRank 
References 
3
0.36
15
Authors
2
Name
Order
Citations
PageRank
Aldo Franco Dragoni121638.16
Ephraim Nissan216421.59