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AIList Digest Volume 5 Issue 113
AIList Digest Monday, 11 May 1987 Volume 5 : Issue 113
Today's Topics:
Conferences - Production Planning, Control &
ICALP '87 &
Matrix of Biology Workshop &
AI and Law, Final Schedule
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Date: Sun, 3 May 1987 18:48 CST
From: Leff (Southern Methodist University)
<E1AR0002%SMUVM1.BITNET@wiscvm.wisc.edu>
Subject: Conferences - Production Planning, Control & ICALP '87
AI at Upcoming Conferences
Expert Systems and the Leading Edge in Production Planning and Control
May 10-13, Charleston, South Carolina
Keynote Addresses
"Managing Knowledge for Production Planning"
Thomas Kehler, Chairman, Intellicorp
"Integration of Manufacturing Policy and Corporate Strategy with the
Aid of Decision Support Systems"
Gabriel Bitran, Professor of Management, Sloan School of Management,
Massachusetts Institutes of Technology
May 11
Tutorial I-- Production Planning and Control
William Berry, University of Iowa
Lee Krajewski, Ohio State University
Tutorial II _ Knowledge-based Expert Systems: Theory and Practice
Mark Fox, Director, Intelligent Systems Laboratory, Carnegie Mellon
University
May 12
Keynote Address
Tracy O'Rouke, President, The Allen Bradley Company
JIT - Then AI
James Butcher, Materials Control Manager, 3M Corporation
Design of Flexible Manufacturing Systems
Kathy Stecke, Operations Management, University of Michigan
Factor Representaiton and Design
Ed Fisher, Department of Industrial Engineering, North Carolina State U.
Exploiting Group Technology in Expert Process Designers
Bruce Johnson, Partner in Charge of Ai, Arthur Anderson
Knowledge-based and Collaborative Design Tools
Sanjay Mittal, Xerox University
An Intelligent Decision Support System for Integrated Distribution Planning
Darwin Klingman and Nancy Phillips,
MIS and Information Systems, University of Texas-Austin
Knowledge-based Simulation and Manufacturing
John Kuntz, Senior Knowledge Systems Engineer, Intellicorp
Panel Discussion:
Integrating Planning Frontiers
Ed Davis, University of Virginia, Jim L. Goedhart, GE Calma
Integration of People, Automation and Computers in Job-Shop Electronics
John Lorei, Manager, Computer INtegrated Manufacturing Rockwell
International
Manufacturing Planning Systems for the 1990s
Thomas Vollman, Department of Operations Management, Boston University
Merrill Ebner, Department of Manufacturing Engineering, Boston University
Artificially Intelligent Tools for Manufacturing Process Planners
Karl Kempf, Senior Computer Scientist, FMC
Panel Discussions:
Workshops in Aerospace Applications for AI, Textile Technology,
Scheduling Applications, Flexible Manufacturing Systems, Product Design
Systems, Advanced Automation (AI and OR)
May 13
Keynote: Rapid Prototyping for Expert Systems
Brian Gaines, Department of Computer Science, University of Calgary
Production Control Issues and Challenges
Steve Melnyk, Management, Michigan State University
FMS Producitoon Planning and Control Problems
Kathy STecke, University of Michigan
>From the ARMF to the Factory of the Future: AI Tools in Process and
Production Planning and Control
Dennis Swyt, Deputy Director, National Bureau of STandards
Using Knowledge Technology to Gain a Competitive Advantage in
Manufacturing
Neil Cahill, Vice President, Manufacturing Technology, Institute of
Textile Technology
Knowlege-Based Process Management Applications
Michael Fehling, Principal Scientist, Rockwell Science Center
Panel Discussion
Scheduling Research: Past, Present, Future
William L. Maxwell, Cornell University
KNowledge-Based Scheduling Systems
Jack Kanet, Clemson University
Knoweldge-Based Scheduling and Resource Allocation in the CAMPS Architecture
Richard Brown, MITRE Corporatio/n
A Knowledge Based Framework for Reactive Management of Factory Schedules
Steve Smith, Intelligent Systems Lab, Carnegie Mellon University
Panel Discussion
Closing Session
%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^%^
ICALP 87, July 13-17, 1987, Karlsruhe, West Germany
July 13
Invited Lecture, Recent Developments in the Theory of Learning,
L. Valiant, Harvard University
Probability and Plurality for Aggregations of Learning Machines,
L. Pitt (University of Illinois), C. H. Smith (University of Maryland)
Inverse Image Analyse
P. Dybjer, University of Goteborg
A Unification Algorithm for Confluent Theories
S. Holldobler, Universitat der Bundeswehr, Munchen
On the Knuth Bendix Completion for Concurrent Processes
V. Diekert, Technische Universitat Munchen
On Word Problems in Equational Theories
J. Hsiang, State University of New York, M. Rusinowitch, CRIN, Vandoeuvre-les-
Nancy
Semantics for nondeterministic, Asynchronous Broadcast Networks
R. K. Shyamasundar, K. T. Narayana, T. Pitassi, Pennsylvania State University
Another Look at Abstraction in Process Algebra
J. C. M. Baeten, University of Amsterdam, R. J. van Glabeek, Centre of
Mathematics and Computer Science, Amsterdam
July 14
Computation Tree Logic CTL* and Path Quantifiers in the MOnadic Theory of
the Binary Tree,
T. Hafer, W. Thomas, RWTH Aachen
Modelchecking of CTL Formulae under Liveness Assumptions
B. Josko, RWTH Aachen
A Model Logic for a Subclass of Event Structures
K. Lodaya, Tata Institute of Fundamental Research Bombay
P. S. Thiagarajan, Aarhus University
Term Matching on Parallel Computers
R. Ramesh, R. M. Verma, T. Krishnaprasad, I. V. Ramakrishnan, SUNY, New York
July 17
Invited Lecture: The Geometry of Robot Motion Planning
J. Schwartz, New York University
Nancy Phillips, Associate Profesor, Department of MIS
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Date: Thu 23 Apr 87 17:34:04-EDT
From: "Patrick H. Winston" <PHW%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Conference - Matrix of Biology Workshop
**************** OPPORTUNITY FOR PARTICIPATION ****************
WORKSHOP
ON THE MATRIX OF
BIOLOGICAL INFORMATION
ARTIFICIAL INTELLIGENCE, DATA BANK MANAGEMENT, COMPUTER ANALYSIS OF
MACROMOLECULES --- APPLIED TO CELLULAR BIOLOGY TO DEVELOP AN APPROACH TO
GENERALIZATIONS AND OTHER THEORETICAL INSIGHTS IN BIOLOGICAL SCIENCE.
We have today a unique opportunity to merge research at the forefront of
Artificial Intelligence with efforts to provide a new conceptual
framework for the laws, models, empirical generalizations and physical
foundations of the modern biological sciences.
The Matrix of Biological Knowledge is an attempt to use advanced
computer methods to organize the immense and growing body of
experimental data in the biological sciences, in the expectation that
there are a significant number of as yet undiscovered ordering
relations, new laws and predictive relations embedded in the mass of
existing information. Workshop participants will attempt to define the
interrelations of the matrix of biological knowledge, and to demonstrate
its feasibility by applying the modern tools of computer science to a
small set of case studies. This is an outgrowth of a report from the
Natl. Academy of Sciences, "Models for Biomedical Research: a New
Perspective," produced in response to a request by the Natl. Institutes
of Health (NIH). A brief summary and description appears in "An
Omnifarious Data Bank for Biology?," SCIENCE 228(4706), 21 June 1985.
The workshop is intended to introduce a number of young scientists to
the matrix concept and to explore with these investigators the
possibilities of new theoretical developments and conceptual frameworks.
The workshop will run July 13 - August 14 at St. Johns College in Santa
Fe, in the Sangre de Cristo mountains of northern New Mexico (AAAI
attendees may miss the first week). Participants will be supported with
housing, meals and travel as necessary. Thirty participants (graduate
students, post-doctoral fellows, and working scientists) are expected to
be selected by application from throughout the United States.
Eight groups will be directed by senior scientists:
"Artificial Intelligence," Patrick Winston, A.I. Laboratory, MIT;
"Management of Large Scale Data Bases," Robert Goldstein, U. Brit. Columbia;
"Computers Applied to Macromolecules," Peter Kollman, U. Cal. San Francisco;
"The Organization of Biological Knowledge," Harold Morowitz, Yale University;
"Cell-Cell Interactions," Hans Bode, U. of Calif., Irvine;
"Toxicology," Robert Rubin, Johns Hopkins University;
"Information Flow from DNA to Cells," Richard Dickerson, UCLA,
Harvey Hershman, UCLA, and Temple Smith, Harvard University;
"Peptides and Signalling Molecules," Christian Burks, Los Alamos Natl. Lab.,
and Derek LeRoith, NIH.
A brief description of background and desire to participate, together
with two letters of recommendation, should be sent to
Santa Fe Institute, attn. Ginger Richardson
P.O. Box 9020
Santa Fe, New Mexico, 87504 - 9020
(phone (505) 984-8800)
(Applicants should first review the NAS report or the SCIENCE article,
above, available in most science libraries.)
The workshop has been previously announced in other forums and the
formal application deadline is 1 May 1987. Applicants who will have
difficulty meeting that deadline should telephone Ginger Richardson and
notify her of their intent to submit an application, as few if any
positions will be available after that date. Applicants are strongly
encouraged to apply expeditiously so that an early decision about
participation may be reached.
Some representative connections between Artificial Intelligence and
the Matrix Workshop follow, but the list is suggestive only.
NATURAL LANGUAGE: What constraints on form and content must be met for
a scientific Abstract to be machine-readable? It is generally a single
paragraph in a very restricted form of declarative prose. If tolerable
constraints could be found they would probably be widely adopted.
KNOWLEDGE REPRESENTATION: How much of what knowledge must be captured,
and how, to enable scientific reasoning? Is a single unified
representation scheme possible or must each sub-field have a specialized
representation to support a specialized vocabulary and ontology? ``In
the Knowledge lies the Power.'' How can we organize this tremendous
amount of knowledge to extract the power everyone believes is there?
ANALOGICAL MAPPING: How can we notice when analogous biological
functions are implemented by analogous structures? Can we discover and
validate analogical animal models of human systems? Can we explain an
unknown response in an organism by analogy to a better-understood
system? Given an experimental system, description or outcome, could we
index and retrieve analogous situations and/or literature references?
MACHINE LEARNING: How can we re-structure the large existing databases
to automate induction from data? Can we use more knowledge-intensive
forms of learning in this knowledge-intensive domain? Can existing
learning paradigms be extended to cope with the noisy data that any real
application must face?
RULE-BASED EXPERT SYSTEMS: How much of the expert scientist's knowledge
can be formalized explicitly as rules? Could we produce an expert
system which, given a problem or request for information, could infer
which database contained the answer? Could expert knowledge, say of
toxicology, be used to produce a Toxicology Advisor which knew how to
access databases to find answers to questions not covered by its rules?
Could we create expert systems which continually scanned new additions
to databases to update their rules, or at least flag areas where the new
addition conflicts with or supplants an existing rules?
TRUTH MAINTENANCE: Suppose an Abstract always contained an explicit
statement of the proposition(s) argued for or against by the paper.
Could this be entered into a dependency network, with the paper as
justification? Could we then query the TMS to determine, for some
proposition, whether it is generally believed, disbelieved, or
controversial; and pick out the relevant literature citations? If a new
paper supports or contradicts a result from a neighboring field, can
this be detected reliably?
QUALITATIVE PROCESS THEORY: Can an organism be modeled as a cooperating
system of processes? Can we organize this so as to find similar process
systems shared by different organisms? Can we reliably predict the
effects of perturbing an organism's processes, e.g. in the study of
toxicology or medicine?
SCIENTIFIC REASONING AND DISCOVERY: We have the opportunity to
structure a large, continuously-updated body of real-world scientific
knowledge. What form of Knowledge Base would best facilitate
discovering the unexpected regularities in the data? Could a program
(possibly using a dependency network of experimental results) suggest
crucial experiments and reason about implications of possible outcomes?
SCHEMA COMPLETION: Can an experiment be understood in terms of a
setting which instantiates an ``experiment schema''? Can we use this to
group results that are ``schematically close'', even if they occur in
different biological models or in related but distinct sub-fields? Can
we fill in the default assumptions underlying a description of the
experiment and results?
DISCOURSE/STORY UNDERSTANDING: Could a scientific article be analyzed
as a narrative describing an experimental setting, a group of
observations, and some conclusions? Given a new story (experiment),
could we retrieve closely related or similar stories we've heard before?
Could a highly abridged summary of the story be produced? Could several
stories be automatically merged, and an overall summary produced?
This list is obviously indicative, not exhaustive.
------------------------------
Date: Fri, 1 May 87 15:23:59 ADT
From: hafner%corwin.ccs.northeastern.edu@RELAY.CS.NET
Subject: Conference - AI and Law, Final Schedule
The First
International Conference on Artificial Intelligence and Law
May 27-29, 1987
Northeastern University, Boston, MA 02115
Sponsored by:
The Center for Law and Computer Science,
Northeastern University
In Cooperation with ACM SIGART
Registration: Ms. Rita Laffey, (617) 437-3346
Information: Prof. Carole Hafner (617) 437-5116
SCHEDULE OF EVENTS
WEDNESDAY, May 27
8:30-12:30 Tutorials
A. "Introduction to Artificial Intelligence (for lawyers)"
Prof. Edwina L. Rissland, University of Massachusetts and
Harvard Law School
B. "Applying Artificial Intelligence to Law: Opportunities
and Challenges"
Profs. Donald H. Berman and Carole D. Hafner, Northeastern
University
2:00-2:30 Welcome; Opening Remarks.
2:30-4:00 Legal Expert Systems I
2:30 "Expert Systems in Law: Out of the Research Laboratory and
into the Marketplace"
Richard E. Susskind
Ernst & Whinney, London, England
3:00 "Expert Systems in Law: The DataLex Project"
Graham Greenleaf, Andrew Mowbray and Alan L. Tyree
University of Sydney, Australia
3:30 "Explanation for an Expert System that Performs Estate
Planning"
Dean A. Schlobohm and Donald A. Waterman
Stanford University, The Rand Corporation
4:00-4:30 Coffee
4:30-6:00 Conceptual Legal Retrieval Systems I
4:30 "Conceptual Legal Document Retrieval Using the RUBRIC System"
Richard M. Tong, Clifford A. Reid, Peter R. Douglas and
Gregory J. Crowe
Advanced Decision Systems
5:00 "Conceptual Organization of Case Law Knowledge Bases"
Carole D. Hafner
Northeastern University
5:30 "Designing Text Retrieval Systems for Conceptual Searching"
Jon Bing
Norwegian Research Center for Computers and Law
6:30-8:30 Welcoming Reception, Northeastern U. Faculty Center
THURSDAY, May 28
9:00-10:30 Models of Legal Reasoning I
9:00 "A Process Specification of Expert Lawyer Reasoning"
D. Peter O'Neil
Harvard Law School
9:30 "A Case-Based System for Trade Secrets Law"
Edwina L. Rissland and Kevin D. Ashley
University of Massachusetts, Amherst
10:00 "But, See, Accord: Generating Blue Book Citations in HYPO"
Kevin D. Ashley and Edwina L. Rissland
University of Massachusetts, Amherst
10:30-11:00 Coffee
11:00-12:30 Legal Expert Systems II
11:00 "A Natural Language Based Legal Expert System for
Consultation and Tutoring -- The LEX Project"
F. Haft, R.P. Jones and Th. Wetter
IBM Heidelberg Scientific Centre, West Germany
11:30 "The Application of Expert Systems Technology to
Case-Based Law"
J.C. Smith and Cal Deedman
University of British Columbia
12:00 "Some Problems in Designing Expert Systems to Aid Legal
Reasoning"
Layman E. Allen and Charles S. Saxon
The University of Michigan, Eastern Michigan University
12:30-2:00 Lunch
2:00-3:00 Panel: "The Impact of Artificial Intelligence on the Legal
System"
Moderator: Cary G. DeBessonet, Law and Artificial Intelligence
Project, Louisiana State Law Institute
3:00-4:00 Conceptual Legal Retrieval Systems II
3:00 "Conceptual Retrieval and Case Law"
Judith P. Dick
University of Toronto
3:30 "A Connectionist Approach to Conceptual Information
Retrieval"
Richard K. Belew
University of California, San Diego
4:00-4:30 Coffee
4:30-6:00 Expert Systems and Tax Law
4:30 "A PROLOG Model of the Income Tax Act of Canada"
David M. Sherman
The Law Society of Upper Canada
5:00 "An Expert System for Screening Employee Pension Plans for
the Internal Revenue Service"
U.S. Internal Revenue Service
Gary Grady and Ramesh S. Patil
5:30 "Handling of Significant Deviations from Boilerplate Text"
U.S. Internal Revenue Service
Gary Morris, Keith Taylor and Maury Harwood
7:00 Reception and Banquet, The Colonnade Hote
Banquet Address: Non-Monotonic Reasoning
Prof. John McCarthy, Stanford University
FRIDAY, May 29
9:00-10:30 Applications of Deontic Logic
9:00 "Legal Reasoning in 3-D"
Marvin Belzer
University of Georgia
9:30 "On the Relationship Between Permission and Obligation"
Andrew J.I. Jones
University of Oslo, Norway
10:00 "System = Program + Users + Law"
Naftaly H. Minsky and David Rozenshtein
Rutgers University
10:30-11:00 Coffee
11:00-12:30 Legal Expert Systems III
11:00 "Support for Policy Makers: Formulating Legislation with
the Aid of Logical Models"
T.J.M. Bench-Capon
Imperial College of Science and Technology, London
11:30 "Logic Programming for Large Scale Applications in Law:
A Formalisation of Supplementary Benefit Legislation"
T.J.M. Bench-Capon, G.O. Robinson, T.W. Routen and
M.J. Sergot
Imperial College of Science and Technology, London
12:00 "Knowledge Representation in DEFAULT: An Attempt to Classify
General Types of Knowledge Used by Legal Experts"
Roger D. Purdy
University of Akron
12:30-2:00 Lunch
2:00-3:00 Panel: Modeling the Legal Reasoning Process: Formal and Computational
Approaches
Moderator: Prof. L. Thorne McCarty, Rutgers University
3:00-4:00 Models of Legal Reasoning II
3:00 "Precedent-Based Legal Reasoning and Knowledge Acquisition
in Contract Law: A Process Model"
Seth R. Goldman, Michael G. Dyer and Margot Flowers
University of California, Los Angeles
3:30 "Reasoning about 'Hard' Cases in Talmudic Law"
Steven S. Weiner
Harvard Law School, MIT
4:00-4:30 Coffee
4:30-6:00 Legal Knowledge Representation
4:30 "OBLOG-2: A Hybrid Knowledge Representation System for
Defeasible Reasoning"
Thomas F. Gordon
GMD, Sankt Augustin, West Germany
5:00 "ESPLEX: A Rule and Conceptual Model for Representing
Statutes"
Carlo Biagioli, Paola Mariani and Daniela Tiscornia
Instituto per la Documentazione Giuridica, Florence, Italy
6:00 "Legal Data Modeling: The Prohibited Transaction Exemption
Analyst"
Keith Bellairs
Computer Law Systems, Inc.
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End of AIList Digest
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