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AIList Digest Volume 6 Issue 058
AIList Digest Tuesday, 29 Mar 1988 Volume 6 : Issue 58
Today's Topics:
Seminars - Learning from Physical Analogies (Ames) &
Explaining Change in Schedules and Budgets (CMU),
Conferences - Expert Systems in Agriculture &
Workshop on use of APL in AI &
ARTISYST: AI for Systematics
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Date: Tue, 22 Mar 88 12:10:30 PST
From: CHIN%PLU@ames-io.ARPA
Subject: Seminar - Learning from Physical Analogies (Ames)
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National Aeronautics and Space Administration
Ames Research Center
SEMINAR ANNOUNCEMENT
SPEAKER: Mr. Brian C. Falkenhainer
University of Illinois
TOPIC: Learning From Physical Analogies
ABSTRACT:
To make programs that understand and interact with the world as well as
people do, we must duplicate the kind of flexibility people exhibit when
conjecturing plausible explanations of the diverse physical phenomena they
encounter. We view this flexibility as arising from an ability to detect
similarities, within and across domains, between the various observed
behaviors. Interpreting an observation often requires the flexible integration
of knowledge from diverse sources and the formation of new theories about
the world. For example, understanding processes such as heat flow and
diffusion may involve reference to known theories of liquid flow, while
explaining the behavior of an oscillating LC electric circuit may require
a knowledge of springs.
Verification-Based Analogical Learning is an approach to theory formation
and revision which relies on analogical inference to hypothesize new theories,
and gedanken experiments (i.e., simulation) to analyze their validity.
It is an iterative process of hypothesis formation, verification, and revision
which focuses on the problem of validating analogically derived models.
This talk will describe the basic elements of verification-based analogical
learning, the kinds of flexible yet constrained reasoning they enable, and
discusses its implications for analogical reasoning in general. A number
of examples from the current implementation, PHINEAS, will be used to explain
and demonstrate the utility and diversity of this approach.
BIOGRAPHY:
Mr. Falkenhainer is a graduate student in the Ph.D program in Philosophy in
Computer Science at the University of Illinois, and is a Research
Assistant in the Qualitative Reasoning Group. His research in artificial
intelligence focuses on the general tasks of theory formation and observation
interpretation. A paper which appeared in the journal, Machine Learning,
summarized the results of his master's thesis on the discovery of functional
relationships in numeric data. A general tool for performing various types
of analogical mappings, called the Structure-Mapping Engine (SME), is
extensively described and analyzed in a paper recently submitted to the
journal, Artificial Intelligence. In support of SME, a probabilistic
generalization to traditional truth-maintenance systems was developed and
is described in a paper from the 1986 workshop on uncertainty in AI.
DATE: Monday, March 28, 1988 TIME: 3:00 - 4:00 pm BLDG. 244 Room 209
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POINT OF CONTACT: Marlene Chin PHONE NUMBER: (415) 694-6525
NET ADDRESS: chin%plu@ames-io.arpa
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VISITORS ARE WELCOME: Register and obtain vehicle pass at Ames Visitor
Reception Building (N-253) or the Security Station near Gate 18. Do not
use the Navy Main Gate.
Non-citizens (except Permanent Residents) must have prior approval from the
Director's Office one week in advance. Submit requests to the point of
contact indicated above. Non-citizens must register at the Visitor
Reception Building. Permanent Residents are required to show Alien
Registration Card at the time of registration.
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Date: Mon, 28 Mar 88 10:39:04 EST
From: Anurag.Acharya@CENTRO.SOAR.CS.CMU.EDU
Subject: Seminar - Explaining Change in Schedules and Budgets (CMU)
AI SEMINAR
TOPIC: Explaining Change in Schedules and Budgets
SPEAKER: Steve Roth (412) 268-7690
DH 3321, The Robotics Institute
Carnegie Mellon University, Pittsburgh, PA 15213
roth@isl1.ri.cmu.edu
WHEN: Tuesday, April 5, 1988 3:30pm
WHERE: Wean Hall 5409
ABSTRACT
This talk will present an approach to the automatic explanation of changes
in the results generated by quantitative project scheduling and budget
systems. Previous experience with CALLISTO, an experimental project
management system, revealed that managers have difficulty isolating and
determining the relationships among changes generated by systems like these.
These systems usually involve large algebraic models with frequently
changing inputs, which managers need to analyze frequently to track the
course of their projects. Our goal was to support this task using techniques
for identifying relevant and significant changes, composing well structured
sequences of assertions for describing these and selecting and composing one
or more graphical styles or pictures of the relevant data.
Our approach accomplishes this by synthesizing three previous approaches:
@i(comparative analysis), a technique for identifying relevant causes of
change in financial models; approaches to text planning based on rhetorical
models (e.g. of descriptions of database structure or justifications of
reasoning for expert systems); and an approach to automatic selection of
displays for conveying quantitative data. Descriptions of change are
generated using combinations of text and graphical displays and therefore
serves as a vehicle for exploring the interaction of the two modes of
presentation and the need for coordination.
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Date: Wed, 23 Mar 88 13:21 EST
From: Thieme@BCO-MULTICS.ARPA
Subject: Conference - Expert Systems in Agriculture
CALL FOR PAPERS
TITLE: Integration of Expert Systems with Conventional Problem Solving
Techniques in Agriculture
SPONSORED BY: AAAI Applied Workshop Series
DESCRIPTION:
Problem solving techniques such as modelling, simulation, optimization,
and network analysis have been used for several years to help agricultural
scientists and practitioners understand and work with biological problems.
By their nature, most of those problems are difficult to define quantita-
tively. In addition many of the models and simulations that have been
developed are not "user-friendly" enough to entice practitioners to use
them. As a result, several scientists are integrating expert system
technology with conventional problem solving techniques in order to increase
robustness of their systems as well to increase usability and to aid in
result interpretation. The goal of this workshop is to investigate the
similarities and differences of leading scientists' approaches and to
develop guidelines for similar work in the future.
CONDITIONS OF PARTICIPATION:
Primary authors (presumably primary investigators) of submitted
manuscripts will be invited to participate in the workshop if their
manuscript is selected. Manuscripts will be submitted in full by JUNE 1,
1988. The manuscripts will be reviewed for originality and clear
presentation of the topic of integration by a committee appointed by the
coordinating committee. Only 40 participants will be selected in order to
maximize free exchange of ideas. The manuscripts will be distributed to
the participants prior to the workshop in order to help them prepare
questions for other authors. The proceedings will be published in a
peer-reviewed journal.
LOCATION AND TIME:
August 10-12, 1987 at the Hyatt Hotel in San Antonio, TX
FOR MORE INFORMATION CONTACT:
Dr. A. Dale Whittaker (409) 845-8379
Agricultural Engineering Department
Texas A&M University WHITTAK at TAMAGEN.BITNET
College Station, TX 77843-2117
Dr. Ronald H. Thieme (617) 671-3772
Honeywell Bull, Inc.
300 Concord Road THIEME at BCO-MULTICS.ARPA
Mail Station 895A
Billerica, MA 01821
Dr. James McKinion (601) 323-2230
Crop Science Research Laboratory
Crop Simulation Research Unit
P.O. Box 5367
Mississippi State, MI 39762-5367
Earl Kline (409) 845-3693
Agricultural Engineering Department
Texas A&M University KLINE at TAMAGEN.BITNET
College Station, TX 77843-2117
------------------------------
Date: 24 Mar 88 19:44:27 GMT
From: portal!cup.portal.com!pcb@uunet.uu.net
Subject: Conference - Workshop on use of APL in AI
WORKSHOP ANNOUNCEMENT
A workshop on APL Techniques in Expert Systems will be held at Syracuse
August 16-20, 1988 under the joint sponsorship of ACM SigAPL and Syracuse
University. The co-chairs are Garth Foster (Dept. of Electrical Engineering and
Information Science) and James Kraemer (School of Business).
The workshop will include group lectures and demonstration plus parallel
hands-on sessions on both mainframe and micro-based systems. Implementation
vehicles include IBM APL2, STSC APL*Plus, and Sharp APL under Unix(TM). Topics
include:
Comparison of rule-based systems: Kenneth Fordyce and Gerald Sullivan, IBM,
Kingston, NY;
Fuzzy sets: Andreas Geyer-Schulz, the Economics University of Vienna;
Associative semantic processing: W. D. Hagamen MD, Cornell Medical College,
New York;
Multi-mode logic: John McInturff, Boeing Advanced Systems, Seattle;
Knowledge-representation case studies with SASNEST: Graeme Jones & David
Bonyun, I.P. Sharp Associates, Ottawa.
The workshop fee is $600; there are discounts for early registration and
to members of ACM or SigAPL. Registration is limited to 50; experience in APL
programming is required. For registration: Dr. Davice Chimene, University
College, Syracuse University, Syracuse, NY 13210; (315) 423-3269. Technical and
program information: Dr. James R. Kraemer, Quantitative Methods, School of
Business, Syracuse University, Syracuse, NY 13210; (315) 423-3747. E-mail:
kraemer@suvm.bitnet
SigAPL Program Committee
3787 Louis Road
Palo Alto, CA 94303-4512
Contact: Paul Berry 415 494-2031
E-mail: pcb on IPSA network;
pcb@cup.portal.com
_______ Unix is a trademark of AT&T - Bell Labs.
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Date: Mon, 28 Mar 88 09:13:53 PST
From: Michael Walker <WALKER@SUMEX-AIM.Stanford.EDU>
Subject: Conference - ARTISYST: AI for Systematics
The ARTISYST Workshop
(ARTificial Intelligence for SYSTematics)
Uses of Artificial Intelligence and modern computer methods for
systematic studies in biology.
Contact: Renaud Fortuner at (916) 445-4521 or through
BITNET or ARPANET at rfortuner@ucdavis.
An organization committee with R. Fortuner, J. Sorensen (Calif. Dept.
of Food & Agriculture), J. Milton, J. Diederich (UC Davis), M. Walker
(Stanford), J. Woolley and N. Stone (Texas A&M) is planning to study
the uses of artificial intelligence and modern computer methods for
systematic studies in biology. This study was suggested by the
Systematic Biology panel of National Science Foundation.
The committee will recruit a group of about twenty systematists, and
about a dozen computer scientists interested in the possible
application of modern computing techniques to a new domain. The
collaborators will meet twice, in early January 1989 and March 1989
during two three-day workshops at University of California, Davis.
During the first workshop the participants will make a list of
questions and problems in systematics that might be solved by modern
computing techniques such as applications of artificial intelligence
in expert systems, computer vision, databases, graphics, etc. After
this initial workshop, small workgroups of specialists from both
fields will collaborate to characterize the options in terms of
computing techniques, and to define the most promising approaches to
their solutions.
During a second workshop, the importance for systematic biology
of each of the problems studied, and the current, short, and long
term availability of relevant computer techniques will be
discussed. A final report will serve as guidelines for NSF
funding for future applications of computer techniques to
systematic biology. The proceedings of both workshops will be
published to serve as a review of state-of-the-art computer
methods that may be of use in systematics.
Systematic biology is the science that studies the relationships among
organisms, and that classifies these organisms according to these
relationships. The National Science Foundation is interested in
supporting the implementation of expert systems and modern computing
techniques for systematic biology. Currently, systematics relies
heavily on statistics and algorithmic computer programming. However,
different computer methods may be used to solve some of its problems.
Expert systems can help with diagnostic identification, correct
application of the rules of nomenclature, etc. Capture of the data
requires computer vision and image analysis. Museum curation and
retrieval of published information could be helped by intelligent
access to large databases. Computer graphics can be used for
identification and teaching. Finally the systematic studies and the
definition of a classification may be helped by intelligent access to
databases and relevant statistics.
The domain of systematic biology is vast and its boundaries are ill
defined. However it is possible to define sub domains that may be
studied separately. First, the organisms to be studied must be
recovered and measured. In this preliminary phase, sub domains
include:
- capture of the data: observation of shapes, measurement of
lengths, angles, areas, position of one feature in relation to
another, etc.
- museum curation: finding specimens relevant to the study
in museum collections by an intelligent search of the collection
records.
- identification of the specimens during field surveys: it
is necessary to know before studying a group of organisms
whether an organism found in the field belongs to this group.
- information retrieval from a variety of published sources.
A second phase is represented by taxonomic analyses of the
relationships existing between organisms and their characteristics.
It includes:
- ontogeny: the study of the development of the embryo, and
the appearance of ancestral features in the embryo that are then
used to support hypotheses on its phylogeny.
- biogeography: geographical distribution of groups of
organisms.
- fossil record: the study of ancestral states of characteristics
and their evolution along a fossil sequence.
- comparative anatomy: comparison of the aspects taken by a
feature in related organisms
- DNA and gene analysis
- definition of apomorphies: search for evolved characters
present in all the members of a group.
- resolution of homoplasies: search for characteristics that
appear similar in two groups, but that are the result of parallel
or convergent evolution rather than originating in a common
ancestor.
- weighting the characteristics: giving more importance to
characteristics that supposedly are strong indicators of
phylogenetic relationships.
- transformation of the raw data: for example, a log
transformation may restore normality.
These analyses result in the ordering of the organisms studied into
groups arranged into some sort of relational networks (trees).
Taxonomic analyses and the construction of trees are in fact
integrated processes, and they may have to be treated as a whole in
the ARTISYST Project. Several methods are in conflict for the
definition of the best methods for the definition of a classification
tree: parsimony (the shortest tree is the best), maximum likelihood
(each taxon is added in turn on the tree where it fits best),
ordination (relies on multi variate analyses), etc. All approaches
make an extensive use of statistics and algorithmic computer
programming but it has been said that most systematic problems cannot
be solved by any algorithm. Availability of expert systems may
suggest other, non- algorithmic, approaches.
Once a tree has been accepted as a working hypothesis, the various
taxa in the tree are named according to the rules of the International
Code of Zoological Nomenclature (or its Botanical correspondent) and
the jurisprudence established over the years by the rulings of the
International Commissions of Zoological or Botanical Nomenclature. It
may be possible to include rules and jurisprudence into an
expert-system similar to legal systems currently under development.
Diagnostic identification is the process through which an unknown
specimen is allotted to its correct place in an existing
classification. This phase is the most promising for the application
of current expert system technology.
Finally, any new method must have a very friendly man-machine
interface to have a chance to be accepted by most systematists.
Each topic will be studied by a small workgroup including one or
several systematists and one or several computer scientists.
Computer scientists interested in participating in this project
should contact Renaud Fortuner at (916) 445-4521 or through
BITNET at rfortuner@ucdavis.
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End of AIList Digest
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