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AIList Digest Volume 5 Issue 080
AIList Digest Monday, 16 Mar 1987 Volume 5 : Issue 80
Today's Topics:
Seminars - Machine Learning: Unifying Principles, Progress (GMR) &
Search Algorithms (CMU) &
Anatomy of a Case-Based Inference (CMU),
Conference - AI and Law (Program and Registration Info)
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Date: Thu, 12 Mar 87 16:41 EST
From: "R. Uthurusamy" <SAMY%gmr.com@RELAY.CS.NET>
Subject: Seminar - Machine Learning: Unifying Principles, Progress (GMR)
Seminar at the General Motors Research Laboratories in Warren, Michigan.
Friday, March 27, 1987 at 10 a.m.
MACHINE LEARNING : UNIFYING PRINCIPLES and RECENT PROGRESS
RYSZARD S. MICHALSKI
Director of the Artificial Intelligence Laboratory and
Professor of Computer Science and Medical Information Science
University of Illinois, Urbana-Champaign, Illinois 61801
Machine learning, a field concerned with developing computational theories
of learning and constructing learning machines, is now one of the most active
research areas in artificial intelligence. An inference-based theory of
learning will be presented that unifies the basic learning strategies.
Special attention will be given to inductive learning strategies, which
include learning from examples and learning from observation and discovery.
We will show that inductive learning can be viewed as a goal-oriented and
resource-constrained inference process. This process draws upon the
learner's background knowledge, and involves a novel type of inference
rules, called 'inductive inference' rules. In contrast with truth-preserving
deductive rules, inductive rules are falsity-preserving.
Several projects conducted at our AI Laboratory at Illinois will be briefly
reviewed, and illustrated by examples from implemented programs.
Non-GMR personnel interested in attending please contact
R. Uthurusamy [ samy@gmr.com ] 313-986-1989
------------------------------
Date: 12 Mar 1987 0717-EST
From: Rich Thomason <THOMASON@C.CS.CMU.EDU>
Subject: Seminar - Search Algorithms (CMU)
COMPUTER SCIENCE COLLOQUIUM PITT/CMU
SPEAKER: David Mutchler (Naval Research Laboratory)
TITLE: What Search Algorithm Gives Optimal Average-Case Performance
When Search Resources Are Highly Limited?
DATE: March 13, 1987
TIME: 1:00 - 2:00 P.M.
PLACE: 228 Alumni Hall, University of Pittsburgh
Searching the state-space for an acceptable solution is a
fundamental activity for many AI programs. Complete search of the
state-space is typically infeasible. Instead, one relies on whatever
heuristic information is available. Here is one interesting question
that then arises: Given n search resources, how can one dynamically
utilize those resources to achieve (on average) as good a solution as
possible?
In this talk, I will:
(1) present a probabilistic model in which to study this
question;
(2) state two theorems that together answer the above
question in the context of that model;
(3) explain how branching processes and branching random
walks are used to prove the theorems.
Here is a brief description of the model I will be using. A
least-cost root-to-leaf path is sought in a random tree. The tree is
known to be binary and complete to depth N. Arc costs are
independently set either to 1 (with probability p) or to 0 (with
probability 1-p). The cost of a leaf is the sum of the arc costs on
the path from the root to that leaf. The searcher (scout) can learn
n arc values; after having done so, a leaf must be selected. It is
easy to see how the leaf should be chosen. The interesting question
is that: how should the scout dynamically allocated the n search
resources to minimize the average cost of the leaf selected?
------------------------------
Date: 13 Mar 87 15:59:55 EST
From: Marcella.Zaragoza@isl1.ri.cmu.edu
Subject: Seminar - Anatomy of a Case-Based Inference (CMU)
AI SEMINAR
TOPIC: "The Anatomy of a Case-Based Inference"
SPEAKER: Janet Kolodner, Georgia Tech
WHEN: Tuesday, March 17, 1987, 3:30 p.m.
WHERE: Wean Hall 5409
***If you wish to meet with the speaker on Tuesday,***
please call Marce at x8818
ABSTRACT: Case-based reasoning is reasoning done on the basis of one
or a set of previous experiences (or cases), rather than from general
reasonable rules. Case-based inference is an inference made from a
previous experience. In this medium, we can look at how case-based
inference can be controlled, requirements for making a careful case-based
inference, and what support mechanisms are necessary to make case-based
inference feasible.
------------------------------
Date: Fri, 13 Mar 87 19:01:56 EST
From: hafner%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: Conference - AI and Law (Program and Registration Info)
The First
International Conference on Artificial Intelligence and Law
May 27-29, 1987
Northeastern University, Boston, Massachusetts
Sponsored by: The Center for Law and Computer Science
Northeastern University
In Co-operation with ACM SIGART
Schedule of Activities:
Wednesday, May 27
8:30 a.m. - 12:30 p.m. - Tutorials
2:00 p.m. - 6:00 p.m. - Research Presentations (see list below)
7:00 p.m. - 10:00 p.m. - Welcoming Reception - NU Faculty Center
Thursday and Friday, May 28-29
8:30 a.m. - 6:00 p.m. - Research Presentations (continued)
Thursday evening, May 28 - 7:00 p.m. - Gala Banquet at the Colonnade Hotel
Tutorials:
A. "Introduction to Artificial Intelligence (For Lawyers)." Edwina L.
Rissland,
Associate Professor of Computer and Information Sciences, University of
Massachusetts at Amherst, and Lecturer in Law, Harvard Law School, will
present the fundamentals of AI from the perspective of a legal expert.
B. "Applying Artificial Intelligence to Law: Opportunities and Challenges."
Donald H. Berman, Richardson Professor of Law, and Carole D. Hafner,
Associate Professor of Computer Science, Northeastern University, will
survey the past accomplishments and current goals of research in AI and Law.
Panels:
"The Impact of Artificial Intelligence on the Legal System."
Moderated by Cary
G. deBessonet, Director of the Law and Artificial Intelligence Project,
Louisiana State Law Institute.
"Modeling the Legal Reasoning Process: Formal and Computational Approaches."
Moderated by L. Thorne McCarty, Professor of Computer Science and Law, Rutgers
University.
List of Research Presentations: (final schedule is not yet determined)
"Expert Systems in Law: The Datalex Project"
Graham Greenleaf, Andrew Mowbray, Alan L. Tyree
Faculty of Law, University of Sydney, AUSTRALIA
"The Application of Expert Systems Technology to Case-Based Law"
J.C. Smith, Cal Deedman
Faculty of Law, University of British Columbia, CANADA
"Legal Reasoning in 3-D"
Marvin Belzer
Advanced Computational Methods Center
University of Georgia, USA
"Explanation for an Expert System that Performs Estate Planning"
Dean A. Schlobohm, Donald A. Waterman
Moraga, California, USA
"Expert Systems in Law: Out of the Research Laboratory and into the
Marketplace"
Richard E. Susskind
Ernst & Whinney
London, ENGLAND
"An Expert System for Screening Employee Pension Plans for the
Internal Revenue Service"
Gary Grady, Ramesh S. Patil
Internal Revenue Service
Washington, D.C. USA
"Conceptual Legal Document Retrieval Using the RUBRIC System"
Richard M. Tong, Clifford A. Reid, Peter R. Douglas, Gregory J. Crowe
Advanced Decision Systems
Mountain View, California USA
"Conceptual Retrieval and Case Law"
Judith P. Dick
Faculty of Library and Information Science, University of Toronto
Toronto, Ontario CANADA
"A Process Specification of Expert Lawyer Reasoning"
D. Peter O'Neill
Harvard Law School
Cambridge, Massachusetts USA
"Conceptual Organization of Case Law Knowledge Bases"
Carole D. Hafner
The Center for Law and Computer Science, Northeastern University
Boston, Massachusetts USA
"A Case-Based System for Trade Secrets Law"
Edwina L. Rissland Kevin D. Ashley
Department of Computer and Information Science,
University of Massachusetts, Amherst, Massachusetts USA
"But, See, Accord: Generating Blue Book Citations in HYPO"
Kevin D. Ashley, Edwina L. Rissland
Department of Computer and Information Science
University of Massachusetts, Amherst Massachusetts USA
"A Connectionist Approach to Conceptual Information Retrieval"
Richard K. Belew
Computer Science and Engineering Department, Univ. of California
San Diego, California USA
"System = Program + Programmers + Law"
Naftaly H. Minsky, David Rozenshtein
Department of Computer Science, Rutgers University
New Brunswick, New Jersey USA
"A Natural Language Based Legal Expert System Project for Consultation
and Tutoring -- The LEX Project"
F. Haft, R.P. Jones, Th. Wetter
IBM Heidelberg Scientific Centre
Heidelberg, WEST GERMANY
"Handling of Significant Deviations from Boilerplate Text in the SPADES
System"
Gary Morris, Keith Taylor, Maury Harwood
Internal Revenue Service
Washington, D.C. USA
"Legal Data Modeling: The Prohibited Transaction Exemption Analyst"
Keith Bellairs
Management Science Department, University of Minnesota
Minneapolis, Minnesota USA
"Reasoning about `Hard' Cases in Talmudic Law
Steven Weiner
Somerville, Massachusetts USA
"Designing Text Retrieval Systems for `Conceptual Searching'"
Jon Bing
Norwegian Research Center for Computers and Law
Oslo, NORWAY
"Support for Policy Makers: Formulating Legislation with the Aid of
Logical Models"
T.J.M. Bench-Capon
Department of Computing, Imperial College
London, ENGLAND
"Further Comments on McCarty's Semantics for Deontic Logic"
Andrew J.I. Jones
University of Oslo
Oslo, NORWAY
"Experiments Using Expert Systems Technology for Teaching Law: Special
Knowledge Representation Approaches in DEFAULT and EVAN"
Roger D. Purdy
School of Law, The University of Akron
Akron, Ohio USA
"OBLOG-2: A Hybrid Knowledge Representation System for Defeasible Reasoning"
Thomas F. Gordon
FS-INFRE, GMD
Sankt Augustin, WEST GERMANY
"ESPLEX: A Rule and Conceptual Model for Representing Statutes"
Carlo Biogioli, Paola Mariana, Daniela Tiscornia
Istituto per la Documentazione Giuridica
Florence, ITALY
"A PROLOG Model of the Income Tax Act of Canada"
David M. Sherman
Maintnix Services
Thornhill, Ontario CANADA
"Some Problems in Designing Expert Systems to Aid Legal Reasoning"
Layman E. Allen, Charles S. Saxon
Law School, The University of Michigan
Ann Arbor, Michigan USA
"Precedent-Based Legal Reasoning and Knowledge Acquisition in Contract Law:
A Process Model"
Seth R. Goldman, Michael G. Dyer, Margot Flowers
Artificial Intelligence Laboratory, University of California, Los Angeles
Los Angeles, California USA
"Logic Programming for Large Scale Applications in Law: A Formalism of
Supplementary Benefit Legislation"
T.J.M. Bench-Capon, G.O. Robinson, T.W. Routen, M.J. Sergot
Department of Computing, Imperial College
London, ENGLAND
___________________________________________________________________________
Program Committee Conference Information
----------------- ----------------------
L.Thorne McCarty, Chair Prof. Carole D. Hafner, Conference Chair
Donald H. Berman (617) 437-5116
Michael G. Dyer Ms. Rita Laffey, Registration
Anne v.d. L. Gardner (617) 437-3346
Edwina L. Rissland
Marek J. Sergot
Housing Information
Special Conference Rates are available at the following hotels:
(Mention "Northeastern University Computers and Law Conference")
1. The Colonnade Hotel - $75 single/$95 double + tax ($8 parking)
120 Huntington Avenue, Boston, MA (617) 424-7000
2. The Midtown Hotel - $58 single/$63 double + tax (includes free parking)
220 Huntington Avenue, Boston, MA (617) 262-1000 or 1-800-343-1177
Both of these hotels are less than a 10-minute walk from the Conference.
Rooms have also been arranged at Boston University dormitories, a
20-minute walk from the conference, or a 10-minute bus ride and a 5-minute
walk. The rates are $29 single/$24 (per person) double. To reserve a
room in the dormitory, use the attached registration form.
SPACE IS LIMITED - RESERVE EARLY!!
Conference Registration Fee (does not include tutorial or banquet)
Regular Full-time Student
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Received by April 20 $95 $55
Received after April 20 $135 $85
Gala Banquest - May 28 ($40/person)
Tutorial Fee: ($50 with conference registration $100 otherwise)
Dormitory Fee ($29/night single, $24/night double)
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End of AIList Digest
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