VERN R. WALKER
Director, Research Laboratory for
Law, Logic & Technology (LLT Lab)
LEGAL REASONING PROJECT
The goal of the Project is to use default logic
to analyze scientific and common-sense reasoning
in legal contexts, particularly in factfinding,
to visualize logic models for evaluating such reasoning, and
to develop software to automate parts of that reasoning.
Hofstra Law's LLT Lab provides an empirical foundation for this Project.
Documentation
The following four articles lay the foundations for the default-logic framework that I have developed
for analyzing legal reasoning - including rule-based reasoning, evidence assessment or evaluation,
and second-order process reasoning.
Discovering the Logic of Legal Reasoning, 35 Hofstra Law Review 1687 (2007)
(arguing the need for a systematic methodology in law). Copy of full text available for download in .pdf format
A Default-Logic Paradigm for Legal Fact-Finding, 47 Jurimetrics 193 (2007)
(documenting the foundational concepts in traditional law-review format).
Copy of full text available for download in .pdf format
Visualizing the Dynamics around the Rule/Evidence Interface in Legal Reasoning, 6 Law, Probability
and Risk 5-22 (2007) (visualizing the elements of the default-logic framework).
Prepublication copy available for download in .pdf format
Emergent Reasoning Structures in Law, in Handbook of Research on Agent-Based Societies:
Social and Cultural Interactions (Goran Trajkovski and Samuel G. Collins, Editors; Idea Group Inc (IGI), 2009)
(viewing the default-logic framework as modeling a knowledge domain with emergent reasoning structures).
Copy of full text available for download in .pdf format
The following article provides an example of the use of the default-logic framework in Hofstra Law's
Research Laboratory for Law, Logic & Technology (LLT Lab).
The article describes the Vaccine/Injury Project Corpus, a collection of legal decisions
awarding or denying compensation for health injuries allegedly due to vaccinations,
together with models of the logical structure of the reasoning of the factfinders in those cases.
This unique corpus provides useful data for formal and informal logic theory, for natural-language research in linguistics,
and for artificial intelligence research. More importantly, the article discusses lessons learned
from developing protocols for manually extracting the logical structure and generating the logic models.
It identifies sub-tasks in the extraction process, discusses challenges to automation,
and provides insights into possible solutions for automation. In particular, the framework and strategies
developed in the article, together with the corpus data, should allow "top–down" and contextual approaches to automation,
which can supplement "bottom-up" linguistic approaches. Illustrations throughout the article use examples drawn from the Corpus.
A framework for the extraction and modeling of fact-finding reasoning from legal decisions:
lessons from the Vaccine/Injury Project Corpus,
19 Artificial Intelligence & Law 291-331 (2011),
with Nathaniel Carie, Courtney C. DeWitt, and Eric Lesh.
Publisher's copy available for download. Review in the New York Law Journal.
Legal Apprentice Software
Apprentice Systems, Inc. (www.apprenticesystems.com) has now made available for free download
a “Student Edition” of its Legal Apprentice software. The software incorporates
the default-logic framework into a software tool for research and education.
(The underlying software has many other applications as well,
which Apprentice Systems is currently developing.)
You can download a free copy of the “Student Edition” from www.legalapprentice.com.
I recommend that you download and read the “Help Document” that accompanies Legal Apprentice,
because its explanation of the software's functions also provides an overview
of the basic ontology of the default-logic framework.
Video Series
I am producing a series of videos that will show how to apply
the default-logic framework and the Legal Apprentice software in research and teaching.
Clicking on the link just below will run the first of these videos,
which I am making available on YouTube.
If you want to be notified as new videos become available,
please email me at vern.r.walker@hofstra.edu.
“WHAT LEGAL RULES LOOK LIKE”
ICAIL 2009
“PLAUSIBILITY SCHEMAS: TEMPLATES FOR LEGAL FACTFINDING”
Research Abstract Presentation and demonstration at the
Twelfth International Conference on ARTIFICIAL INTELLIGENCE and LAW
8th - 12th June 2009
Institute of Law and Technology, Autonomous University of Barcelona
Barcelona, Spain
Click here to go to the Course and Demonstration Page for the Presentation
Sant’Anna Seminar 2009
“BUILDING LEGAL REASONING TREES”
“ASSESSING THE PROBATIVE VALUE OF EVIDENCE”
Seminar and Lectures
Scuola Superiore Sant’Anna; Pisa, Italy
4 - 14 May 2009
This seminar and course of lectures constituted an intensive, interactive workshop
in the logical analysis and modeling of legal reasoning.
The workshop combined theory and skills,
employed newly-developed modeling software,
and took a problem-based, stepped approach to learning.
A major goal of the workshop was to teach and use a methodology
for conducting empirical research into legal reasoning.
Another goal was to explore the usefulness of software
for making legal reasoning more transparent, consistent, effective, and efficient.
Click here to go the Course Page for Week One
Click here to go the Course Page for Week Two
Sant’Anna Seminar 2008
“LAWYERS, JUDGES, REGULATORS AND SCIENTISTS:
USING THE PRECAUTIONARY PRINCIPLE TO DECIDE LEGAL CASES”
Seminar and Lectures
Scuola Superiore Sant’Anna; Pisa, Italy
5 - 8 May 2008
Click here to view the Course Description
NOTE: The following videos are in Quicktime format, and can be viewed with a Quicktime viewer.
File sizes are large, so downloading over a fast Internet connection is recommended.
If you need to download a free Quicktime viewer, please go to: http://www.apple.com/downloads/.
Each of the four days of the course presented a single "story," and each day had its own themes.
Lecture 1, an introduction to modeling the logic of legal reasoning, with a focus on the modeling of legal rules.
Click below on Part 1 (95.8 MB) or Part 2 (65.3 MB) to download/view the audio-slide videos.
For a description of Lecture 1, click here.
Lecture 2, the story of the explosive growth of law, and why the rule structure of law almost always expands.
Click below on Part 1 (112.7 MB) or Part 2 (132.5 MB) to download/view the audio-slide videos.
For a description of Lecture 2, click here.
Lecture 3, an introduction to modeling the logic of evidence assessment or evidence evaluation,
with particular focus on the role of science in legal reasoning.
Click below on Part 1 (139.9 MB) or Part 2 (104.2 MB) to download/view the audio-slide videos.
For a description of Lecture 3, click here.
Lecture 4, a survey of the cutting edge of research using the default-logic framework, as well as some elements of future work.
Click below on Part 1 (125.6 MB) or Part 2 (84.0 MB) to download/view the audio-slide videos.
For a description of Lecture 4, click here.
AAAI 2006 and Earlier Work
PLEASE NOTE: Some of the videos below this point on the page
are packaged with their own viewers that run on Windows PCs, and it may be necessary
to save the video file to your own computer and then open it by double-clicking on it.
These videos are not currently available in Quicktime format.
ASSOCIATION FOR THE ADVANCEMENT OF ARTIFICIAL INTELLIGENCE
PRESENTATION AT THE FALL SYMPOSIUM 2006 (October 13-15)
“A DEFAULT-LOGIC FRAMEWORK FOR LEGAL REASONING IN MULTIAGENT SYSTEMS”
Abstract
Using law and evidence to achieve fair and accurate decisions in numerous legal cases
requires a complex multiagent system. This paper discusses a framework based on
many-valued, predicate, default logic that successfully captures legal knowledge,
integrates and evaluates expert and non-expert evidence, coordinates agents
working on different legal problems, and evolves the knowledge model over time.
The graphical syntax and the semantics of this framework allow the automation
of key tasks, and the emergence of dynamic structures for integrating human and
non-human agents. The logical basis of the framework ensures its applicability to
knowledge and problem domains of similar complexity to law.
The final version of the paper can be downloaded using the following links:
AAAI Fall 2006 Paper in MS Word Format
AAAI Fall 2006 Paper in PDF Format
A screen-cam video of the presentation can be downloaded using the following links.
The video is in three parts, to keep the size of the files manageable.
The first set of three videos is in *.avi format, without a built-in viewer,
while the second set of three videos have a high-quality, built-in viewer that runs on Windows.
Walker AAAI 2006 Presentation, Video Part I of III (17 MB, in *.avi format)
Walker AAAI 2006 Presentation, Video Part II of III (27 MB, in *.avi format)
Walker AAAI 2006 Presentation, Video Part III of III (11 MB, in *.avi format)
Walker AAAI 2006 Presentation, Video Part I of III (18 MB, with built-in viewer for Windows)
Walker AAAI 2006 Presentation, Video Part II of III (24 MB, with built-in viewer for Windows)
Walker AAAI 2006 Presentation, Video Part III of III (8 MB, with built-in viewer for Windows)
OVERVIEW OF MY WORK ON LEGAL REASONING (JULY 2005)
Screen Cam: An Overview of My Work on Legal Reasoning (July 2005)
EARLY LEGAL APPRENTICE SOFTWARE
Software Description: The early, experimental software (developed for legal applications by Apprentice Systems, Inc.) shown in the following videos implements legal reasoning on an artificial intelligence platform. More recent work, using the .NET/XML framework, has superseded the early versions shown below. Nevertheless, the early work still provides insight into the structure of legal argument. For example, we are forced to define the functional relationships among legal rules, policies, and evidence, in order to integrate them into the factfinding process.
Video on Early Legal Apprentice Software: Introduction
Video on Early Legal Apprentice Software: Basic Authoring Tools
Video on Early Legal Apprentice Software: Legal Implication Trees
Video on Early Legal Apprentice Software: Evaluation Mode
Video on Early Legal Apprentice Software: Case Profiles and Argument Generator
LEGAL REASONING APPLICATIONS IN TORT LAW
Tort law provides an important and informative field of application for legal reasoning. As I develop videos and demonstrations of such applications, I will make them available below.
Video on Extracting Legal Rules from Cases: Robinson v. Lindsay
Video on the Logical Structure of Legal Argument
RESUME COURSES PUBLICATIONS MAJOR PRESENTATIONS
Return to Vern R. Walker Home Page.