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AIList Digest Volume 4 Issue 207
AIList Digest Tuesday, 7 Oct 1986 Volume 4 : Issue 207
Today's Topics:
Seminars - Cross-Talk in Mental Operations (UCB) &
Deductive Databases (UPenn) &
Concept Acquisition in Noisy Environments (SRI) &
Prolog without Horns (CMU) &
Knowledge Engineering and Ontological Structure (SU),
Conferences - AAAI-87 Tutorials &
1st Conf. on Neural Networks &
Workshop on Qualitative Physics
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Date: Mon, 6 Oct 86 15:38:02 PDT
From: admin%cogsci.Berkeley.EDU@berkeley.edu (Cognitive Science Program)
Subject: Seminar - Cross-Talk in Mental Operations (UCB)
BERKELEY COGNITIVE SCIENCE PROGRAM
Cognitive Science Seminar - IDS 237A
Tuesday, October 14, 11:00 - 12:30
2515 Tolman Hall
Discussion: 12:30 - 1:30
2515 Tolman Hall
``Cross-Talk and Backward Processing in Mental Operations''
Daniel Kahneman
Psychology Department
There are many indications that we only have imperfect
control of the operations of our mind. It is common to compute
far more than is necessary for the task at hand. An operation
of cleaning-up and inhibition of inappropriate responses is
often required, and this operation is often only partially suc-
cessful. For example, we cannot stop ourselves from reading
words that we attend to; when asked to assess the similarity of
two objects in a specified attribute we apparently compute many
similarity relations in addition to the requisite one. The
prevalence of such cross-talk has significant implications for
a psychologically realistic notion of meaning for the interpre-
tation of incoherence in judgments.
A standard view of cognitive function is that the objects
and events of expeience are assimilated, more or less success-
fully, to existing schemas and expectations. Some perceptual
and cognitive phenomena seem to fit another model, in which
objects and events elicit their own context and define their
own alternatives. Surprise, for example, is better viewed as a
failure to make sense of an event post hoc than as a violation
of expectations. Some rules by which events evoke counterfac-
tual alternatives to themselves will be described.
------------------------------
Date: Sun, 5 Oct 86 11:15 EDT
From: Tim Finin <Tim@cis.upenn.edu>
Subject: Seminar - Deductive Databases (UPenn)
3:00pm, Tuesday, October 7, 1986
23 Moore School, University of Pennsylvania
EFFICIENT DEDUCTIVE DATABASES
WILL THEY EVER BE CONSTRUCTED?
Tomasz Imielinski
Rutgers University
The area of deductive databases is a rapidly growing field concerned with
enhancing traditional relational databases with automated deduction
capabilities. Because of the large amounts of data involved here the
complexity issues become critical. We present a number of results related to
the complexity of query processing in the deductive databases, both with
complete and incomplete information.
In an attempt to answer the question of whether efficient deductive databases
will ever be constructed we demonstrate an idea of the "deductive database of
the future". In such a system the concept of an answer to a query is tailored
to the various limitations of computational resources.
------------------------------
Date: Mon 6 Oct 86 16:25:34-PDT
From: Joani Ichiki <ICHIKI@SRI-STRIPE.ARPA>
Subject: Seminar - Concept Acquisition in Noisy Environments (SRI)
L. Saitta (Dipartimento di Informatica, Universita di Torino, Italy)
will present his talk entitled, "AUTOMATED CONCEPT ACQUISITION IN
NOISY ENVIRONMENTS," 10/7/86 in EK242 at 11:00am. Abstract follows.
This paper presents a system which performs automated concept
acquisition from examples and has been especially designed to work in
errorful and noisy environments.
The adopted learning methodology is aimed to the target problem of
finding discriminant descriptions of a given set of concepts and both
examples and counterexamples are used.
The learning knowledge is expressed in the form of production rules,
organized into separate clusters, linked together in a graph
structure; the condition part of the rules, corresponding to
descriptions of relevant aspects of the concepts, is expressed by
means of a first order logic based language, enriched with constructs
suitable to handle uncertainty and vagueness and to increase
readability by a human user. A continuous-valued semantics is
associated to this language and each rule is affected by a certainty
factor.
Learning is considered as a cyclic process of knowledge extraction,
validation and refinement; the control of the cycle is left to the
teacher.
Knowledge extraction proceeds through a process of specialization,
rather than generalization, and utilizes a technique of problem
reduction to contain the computational complexity. Moreover, the
search strategy is strongly focalized by means of task-oriented but
domain-independent heuristics, trying to emulate the learning
mechanism of a human being, faced to find discrimination rules from a
set of examples.
Several criteria are proposed for evaluating the acquired knowledge;
these criteria are used to guide the process of knowledge refinement.
The methodology has been tested on a problem in the field of speech
recognition and the obtained experimental results are reported and
discussed.
------------------------------
Date: 6 October 1986 1411-EDT
From: Peter Andrews@A.CS.CMU.EDU
Subject: Seminar - Prolog without Horns (CMU)
The following talk will be given in the Seminar on Automated
Reasoning Wednesday, Oct. 15, at 4:30p.m. in room PH125C. The talk
is independent of preceding material in the seminar.
Prolog without Horns
D. W. Loveland
An extension to Prolog is defined that handles non-Horn clause sets
(programs) in a manner closer to standard Prolog than previously
proposed. Neither the negation symbol or a symbol for false are
formally introduced in the system, although the system is
conjectured to be propositionally complete. The intention of the
extension is to provide processing of "nearly Horn" programs with
minimal deviation from the Prolog format. Although knowledge of
Prolog is not essential, some prior exposure to Prolog will be helpful.
------------------------------
Date: Mon 6 Oct 86 16:55:52-PDT
From: Lynne Hollander <HOLLANDER@SUMEX-AIM.ARPA>
Subject: Seminar - Knowledge Engineering and Ontological Structure (SU)
SIGLUNCH
Title: KNOWLEDGE ENGINEERING AS THE INVESTIGATION OF
ONTOLOGICAL STRUCTURE
Speaker: Michael J. Freiling
Computer Research Laboratory
Tektronix Laboratories
Place: Chemistry Gazebo
Time: 12:05-1:15, Friday, October 10
Experience has shown that much of the difficulty of learning to build
knowledge-based systems lies in designing representation structures that
adequately capture the necessary forms of knowledge. Ontological analysis
is a method we have found quite useful at Tektronix for analyzing and
designing knowledge-based systems. The basic approach of ontological
analysis is a step-by-step construction of knowledge structures beginning
with simple objects and relationships in the task domain, and continuing
through representations of state, state transformations, and heuristics
for selecting transformations. Formal tools that can be usefully employed
in ontological analysis include domain equations, semantic grammars, and
full-scale specification languages. The principles and tools of
ontological analysis are illustrated with actual examples from
knowledge-based systems we have built or analyzed with this method.
------------------------------
Date: Mon 29 Sep 86 10:39:41-PDT
From: William J. Clancey <CLANCEY@SUMEX-AIM.ARPA>
Subject: AAAI-87 Tutorials
AAAI-87 Tutorials -- Request for Proposals
Tutorials will be presented at AAAI-87/Seattle on Monday, Tuesday, and
Thursday, July 13, 14, and 16. Anyone interested in presenting a tutorial
on a new or standard topic should contact the Tutorial Chair, Bill Clancey.
Topic suggestions from tutorial attendees are also welcome.
Potential speakers should submit a brief resume covering relevant background
(primarily teaching experience) and any available examples of work (ideally,
a published tutorial-level article on the subject). In addition, those
people suggesting a new or revised topic should offer a 1-page summary of
the idea, outlining the proposed subject and depth of coverage, identifying
the necessary background, and indicating why it is felt that the topic would
be well attended.
With regard to new courses, please keep in mind that tutorials are intended
to provide dissemination of reasonably well-agreed-upon information, that
is, there should be a substantial body of accepted material. We especially
encourage submission of proposals for new advanced topics, which in 1986
included "Qualitiative Simulation," "AI Machines," and "Uncertainty
Management."
Decisions about topics and speakers will be made by November 1. Speakers
should be prepared to submit completed course material by December 15.
Bill Clancey
Stanford Knowledge Systems Laboratory
701 Welch Road, Building C
Palo Alto, CA 94304
Clancey@SUMEX
------------------------------
Date: Tue, 30 Sep 86 11:43:56 pdt
From: mikeb@nprdc.arpa (Mike Blackburn)
Subject: 1st Conf. on Neural Networks
CONFERENCE ANNOUNCEMENT: FIRST ANNUAL
INTERNATIONAL CONFERENCE ON NEURAL NETWORKS
San Diego, California
21-24 June 1987
The San Diego IEEE Section welcomes neural network
enthusiasts in industry, academia, and government world-wide
to participate in the inaugural annual ICNN conference in
San Diego.
Papers are solicited on the following topics:
* Network Architectures * Learning Algorithms * Self-
Organization * Adaptive Resonance * Dynamical Network
Stability * Neurobiological Connections * Cognitive
Science Connections * Electrical Neurocomputers * Opti-
cal Neurocomputers * Knowledge Processing * Vision *
Speech Recognition & Synthesis * Robotics * Novel
Applications
Contributed Papers: Extended Abstract should be submitted by
1 February 1987 for Conference Presentation. The Abstract
must be single spaced, three to four pages on 8.5 x 11 inch
paper with 1.5 inch margins. Abstracts will be carefully
refereed. Accepted abstracts will be distributed at the
conference. Final Papers due 1 June 1986.
FINAL RELEASE OF ABSTRACTS AND PAPERS WITH RESPECT TO
PROPRIETARY RIGHTS AND CLASSIFICATION MUST BE OBTAINED
BEFORE SUBMITTAL.
Address all Corresspondence to: Maureen Caudill - ICNN
10615G Tierrasanta Blvd. Suite 346, San Diego, CA 92124.
Registration Fee: $350 if received by 1 December 1986, $450
thereafter.
Conference Venue: Sheraton Harbor Island Hotel (approx. $95
- single), space limited, phone (619) 291-6400. Other lodg-
ing within 10 minutes.
Tutorials and Exhibits: Several Tutorials are Planned. Ven-
dor Exhibit Space Available - make reservations early.
Conference Chairman: Stephen Grossberg
International Chairman: Teuvo Kohonen
Organizing Committee: Kunihiko Fukushima, Clark Guest,
Robert Hecht-Nielsen, Morris Hirsch, Bart Kosko (Chairman
619-457-5550), Bernard Widrow.
September 30, 1986
------------------------------
Date: 5 Oct 1986 13:16 EDT (Sun)
From: "Daniel S. Weld" <WELD%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Workshop on Qualitative Physics
Call for Participation
Workshop on Qualitative Physics
May 27-29, 1987
Urbana, Illinois
Sponsored by:
the American Association for Artificial Intelligence
and
Qualitative Reasoning Group
University of Illinois at Urbana-Champaign
Organizing Committee:
Ken Forbus (University of Illinois)
Johan de Kleer (Xerox PARC)
Jeff Shrager (Xerox PARC)
Dan Weld (MIT AI Lab)
Objectives:
Qualitative Physics, the subarea of artificial intelligence concerned with
formalizing reasoning about the physical world, has become an important and
rapidly expanding topic of research. The goal of this workshop is to
provide an opportunity for researchers in the area to communicate results
and exchange ideas. Relevant topics of discussion include:
-- Foundational research in qualitative physics
-- Implementation techniques
-- Applications of qualitative physics
-- Connections with other areas of AI
(e.g., machine learning, robotics)
Attendance: Attendence at the workshop will be limited in order to maximize
interaction. Consequently, attendence will be by invitation only. If you
are interested in attending, please submit an extended abstract (no more
than six pages) describing the work you wish to present. The extended
abstracts will be reviewed by the organizing committee. No proceedings will
be published; however, a selected subset of attendees will be invited to
contribute papers to a special issue of the International Journal of
Artificial Intelligence in Engineering.
Requirements: The deadline for submitting extended abstracts is February
10th. On-line submissions are not allowed; hard copy only please. Since
no proceedings will be produced, abstracts describing papers submitted to
AAAI-87 are acceptable. Invitations will be sent out on March 1st. Please
send 6 copies of your extended abstracts to:
Kenneth D. Forbus
Qualitative Reasoning Group
University of Illinois
1304 W. Springfield Avenue
Urbana, Illinois, 61801
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End of AIList Digest
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