• Publications
  • Influence
Modeling legal argument - reasoning with cases and hypotheticals
  • Kevin D. Ashley
  • Computer Science
  • Artificial intelligence and legal reasoning
  • 21 February 1991
This dissertation is about adversarial, case-based reasoning and the HYPO program that performs adversarial reasoning with cases and hypotheticals in the legal domain and addresses issues of central concern to Artificial Intelligence. Expand
Predicting outcomes of case based legal arguments
An empirical evaluation of IBP is described, in which the algorithm is compared to prediction based on Hypo's and CATO's relevance criteria, and to a number of widely used machine learning algorithms. Expand
Reasoning with Cases and Hypotheticals in HYPO
HYPO's reasoning process and various computational definitions are described and illustrated, including its definitions for computing relevant similarities and differences, the most on point and best cases to cite, four kinds of counter-examples, targets for hypotheticals and the aspects of a case that are salient in various argument roles. Expand
Modelling Legal Argument: Reasoning with Cases and Hypotheticals, a Thesis Proposal.
The program comprises a means of representing and indexing cases in a Case Knowledge Base (CKB), a computational definition of relevance in terms of dimensions which capture the utility of a case for making a particular kind of argument, and a dimension-based method for other cases. Expand
Defining "Ill-Defined Domains"; A literature survey.
In order to make progress on Intelligent Tutoring in ill-defined domains it is helpful to start with a definition. In this paper we consider the existing definitions and select one for the basis ofExpand
Automatically classifying case texts and predicting outcomes
This paper provides an extended example illustrating both functions, prediction by IBP and text classification by SMILE, and reports empirical evaluations of each. Expand
A case-based system for trade secrets law
An overview of the case-based reasoning program, HYPO, which operates in the field of trade secret law, and an extended example of HYPO working through a hypothetical trade secrets case, patterned after an actual case. Expand
Textual case-based reasoning
This commentary provides a definition of textual case-based reasoning (TCBR) and surveys research contributions according to four research questions, and concludes with potential directions for TCBR research. Expand
A case-based approach to modeling legal expertise
The authors demonstrate how Hypo critically compares a problem situation to the most relevantly similar precedent cases to outline an argument regarding how to decide the current fact situation based on its significant similarities to and differences from most on point cases. Expand
Evaluating a learning environment for case-based argumentation skills
Evaluating CAT0 in the context of a second-semester Iegal writing course taught at the University of Pittsburgh School of Law found that 7.5 hours of CAT0 instruction led to a statistically significant improvement in students’ basic argumentation skills, comparable to that achieved by an experienced legal writing instructor teaching small groups of students in a more traditional way. Expand