Skip to main content Accessibility help
×
Hostname: page-component-77c89778f8-m42fx Total loading time: 0 Render date: 2024-07-21T06:28:51.802Z Has data issue: false hasContentIssue false

5 - Computational Models of Legal Argument

from PART I - COMPUTATIONAL MODELS OF LEGAL REASONING

Published online by Cambridge University Press:  13 July 2017

Kevin D. Ashley
Affiliation:
University of Pittsburgh
Get access

Summary

INTRODUCTION

In the last decades, much of the AI & Law research community has focused on developing comprehensive computational models of legal argumentation (CMLAs). Researchers have now integrated into these CMLAs a number of the computational models of legal reasoning presented in the preceding chapters.

An argument model consists of a representation of the elements of an argument and a specification of its semantics. Argument elements include the argument itself and, possibly, statements or propositions in the argument, as well as their interrelations, for example as constituents of argument graphs. The argument semantics are specified through some well-defined process by which the status of the argument elements can be determined, for example, by inspection of the graph.

Researchers in AI have produced a variety of argument models that differ widely in the aspects of arguments they represent and in the way they specify the status of an argument.

For example, abstract argument systems, including the pioneering Dungean models, abstract away much of the structure of argumentation, simply representing arguments and attack relations between them (Dung, 1995). They specify criteria for determining the status of an argument, that is, whether an argument is acceptable, in terms of the absence of attacking arguments that are not themselves attacked. One can extend Dungean models to account for more complex argument phenomena. For instance, a widely used computational model of argument, ASPIC+, represents premises and conclusions and takes into account support as well as attack relations (Modgil and Prakken, 2014). The Value-based Argumentation Framework (VAF) (Section 5.4) also demonstrates building more complex argument phenomena, arguing about underlying values, and extending Dungean models.

Other argument models are designed to preserve structural aspects of arguments that may make them more intuitively accessible to practitioners. For example, Verheij (2009) has developed models of legal argument that employ the familiar Toulmin argument structures relating claims and evidence via warrants and backing. The Carneades model, discussed in Section 5.2, also preserves an intuitively accessible structure clearly distinguishing propositions and arguments that support a conclusion from those that attack it.

Type
Chapter
Information
Artificial Intelligence and Legal Analytics
New Tools for Law Practice in the Digital Age
, pp. 127 - 168
Publisher: Cambridge University Press
Print publication year: 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×