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AIList Digest Volume 6 Issue 024
AIList Digest Friday, 5 Feb 1988 Volume 6 : Issue 24
Today's Topics:
Seminars - Emerald: Object-Based Distributed Programming (SU) &
Non-Atomic Concurrency Control (SU) &
Capacity of Associative Memory Models (HP) &
Reasoning about Reliability (SRI) &
Synthesizing Context-Dependent Plans (BBN) &
AI, NL, and Object-Oriented Databases at HP (NASA),
Conference - Connectionist Modeling and Brain Function (Princeton),
Course - Connectionist Summer School
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Date: Sat, 30 Jan 88 17:15:09 PST
From: Bruce L Hitson <hitson@Pescadero.stanford.edu>
Subject: Seminar - Emerald: Object-Based Distributed Programming (SU)
EMERALD: AN OBJECT-BASED LANGUAGE FOR DISTRIBUTED PROGRAMMING
Henry M. Levy
University of Washington
DSRS: Distributed Systems Research Seminar (CS548)
Thursday, February 4, 4:15pm
Margaret Jacks Hall 352
Despite the existence of many distributed systems, programming
distributed applications is still a complex task. We have designed
a new object-based language called Emerald to simplify distributed
programming. The novel features of Emerald include (1) a single
object model used for programming both small local objects and large
distributed objects, (2) support for abstract types, and (3) an
explicit notion of location and mobility. While local and
remote Emerald objects are semantically identical, the compiler
is able to select from several implementation styles; Emerald provides
performance commensurate with procedural languages in the local case
and with remote procedure call systems in the remote case. The
Emerald system has been prototyped on a small local area network
of MicroVAX IIs running Ultrix.
This talk will give an overview of the Emerald project and the design of
the Emerald language and run-time kernel.
------------------------------
Date: Sun 31 Jan 88 14:19:58-PST
From: Anil R. Gangolli <GANGOLLI@Sushi.Stanford.EDU>
Subject: Seminar - Non-Atomic Concurrency Control (SU)
4-February-1988: Nir Shavit
Toward a Non-Atomic Era:
L-Exclusion as a Test Case
Most of the research in concurrency control has been based on the
existence of strong synchronization primitives such as test and set.
Following Lamport, recent research promoting the use of weaker
``safe'' rather then ``atomic'' primitives has resulted in
construction of atomic registers from safe ones, in the belief that
they would be useful tools for process synchronization. It has been
shown that using such atomic registers it is impossible to create
strong synchronization primitives such as test and set. We therefore
advocate a different approach, to skip the intermediate step of
achieving atomicity, and solve problems directly from safe registers.
We show how to achieve a fair solution to $\ell$-exclusion, a problem
previously solved assuming a very powerful form of test and set. We
do so using safe registers alone and without introducing atomicity.
The solution is based on the construction of simple novel
synchronization primitives that are non-atomic.
*** Time and Place: 12:30pm, Th, Feb. 4, Margaret Jacks Hall (MJH), Room 352
------------------------------
Date: Mon, 1 Feb 88 09:29:13 PST
From: COE%PLU@ames-io.ARPA
Subject: Seminar - Capacity of Associative Memory Models (HP)
*********************** OPEN TECHNICAL MEETING ***********************
IEEE Computer Society, Santa Clara Valley Chapter
Tuesday Febuary 9, 1988 8:00 p.m.
Hewlett-Packard Cupertino (Wolfe & Homestead)
Building 48, Oak Room
"CAPACITY FOR PATTERNS AND SEQUENCES IN KANERVA'S SDM AS COMPARED TO
OTHER ASSOCIATIVE MEMORY MODELS"
ABSTRACT: Dr. James Keeler of Stanford University will be speaking on the
information capacity of Kanerva's Sparse, Distributed Memory
(SDM) and Hopfield-type neural networks will be discussed. Using
certain approximations, it is shown that the total information
stored in these systems is proportional to the number connections
in the network. The proportionality constant is the same for the
SDM and Hopfield-type models independent of the particular model,
or the order of the model. This same analysis can be used to show
that the SDM can store sequences of spatiotemporal patterns, and
the addition of time-delayed connections allows the retrieval of
context dependent temporal patterns with varying time delays.
Dr. Keeler Received his Ph.D in Physics from U. C. San Diego, March 1987.
His dissertation was on reaction-diffusion systems and neural network models.
He is now a Postdoctoral student at Stanford University's Department of
Chemistry working on neural network models, as well as consulting for Penti
Kanerva's (RIACS, NASA Ames Research Center) SDM research group.
For additional information contact Coe Miles-Schlichting:
coe@pluto.arc.nasa.gov or (408) 279-4773
------------------------------
Date: Mon, 1 Feb 88 15:28:23 PST
From: seminars@csl.sri.com (contact lunt@csl.sri.com)
Subject: Seminar - Reasoning about Reliability (SRI)
SRI COMPUTER SCIENCE LAB SEMINAR ANNOUNCEMENT:
Unified Diagnosis for Reliability Enhancement in Real-Time Systems
Roy A. Maxion
Department of Computer Science
Carnegie Mellon University
Pittsburgh, Pennsylvania
Friday, February 5 at 4:00 pm
SRI International, Room AD202, Building A
The intuitive sense of reliability is availability. To most users, if a
system is available for its specified purpose at the moment the user (or
other process) wishes to use it, then the system is perceived as being
reliable. Hence high availability can be used to enhance the perception of
high reliability. When a system fails, then, it is important to restore
service, or availability, as quickly as possible.
Diagnosis is an important response to system failure. In critical applications
that demand high reliability, such as process control systems or hospital
patient-monitoring systems, a swift and accurate failure diagnosis and
subsequent prescription for remediation can provide the operating margin
necessary for maintaining operational reliability. Diagnosis, usually a
retrospective technique, can also be employed predictively to avoid certain
classes of failure.
This talk presents an architecture that supports an empirical testbed for a
unified theory of diagnostic reasoning. The testbed supports theoretical
modeling as well as practical applications; the underlying diagnostic engine
can be fine tuned, and the practical performance results can be subsequently
observed. Machine learning is an integral part of the system, enabling the
system to tune itself to its environment. The testbed has been migrated
to a real-world environment -- the 5,000 station nonhomogeneous campus
computing network at Carnegie Mellon University -- and used in real-time
detection and diagnosis of network failures. Examples and explanations of
problems discovered and diagnosed by the system will be presented.
In discussing his talk, the author noted that a central issue in his
approach is how to define expected behavior so that a monitor may
justifiably decide that system behavior is worthy of detailed
diagnosis (Jack Goldberg).
NOTE FOR VISITORS TO SRI:
Please arrive at least 15 minutes early in order to sign in and
be shown to the conference room. Those not arriving by 4pm may
not be able to attend the talk.
SRI is located at 333 Ravenswood Avenue in Menlo Park. Visitors
may park in the visitors lot in front of Building A (red brick
building at 333 Ravenswood Ave) or in the conference parking area
at the corner of Ravenswood and Middlefield. The seminar room is in
Building A. Visitors should sign in at the reception desk in the
Building A lobby.
IMPORTANT: Visitors from Communist Bloc countries should make the
necessary arrangements with Fran Leonard, SRI Security Office,
(415) 859-4124, as soon as possible.
UPCOMING SRI COMPUTER SCIENCE LAB SEMINARS:
Monday, February 8 at 4pm, Arthur Keller of Stanford University and
the University of Texas at Austin will speak on a "Framework for the
Security Component of an Ada* DBMS." Room IS109, in the International
Building.
Thursday, February 11 at 4pm, Janice Glasgow of Queen's University,
Kingston Ontario, will speak on "A Formal Model for Reasoning About
Distributed Systems." Conference Room B, Building A.
------------------------------
Date: Wed 3 Feb 88 16:38:18-EST
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: Seminar - Synthesizing Context-Dependent Plans (BBN)
BBN Science Development Program
AI Seminar Series Lecture
SYNTHESIZING PLANS THAT CONTAIN ACTIONS
WITH CONTEXT-DEPENDENT EFFECTS
Edwin P.D. Pednault
AT&T Bell Laboratories
Holmdel, New Jersey
(!vax135!epdp@UCBVAX.BERKELEY.EDU)
BBN Labs
10 Moulton Street
3rd floor large conference room
10:30 am, Tuesday February 9th
*********************
* note unusual room *
*********************
Conventional domain-independent planning systems have typically excluded
actions whose effects depend on the situations in which they occur,
largely because of the action representations that are employed.
However, some of the more interesting actions in the real world have
context-dependent effects. In this talk, I will present a planning
technique that specifically addresses such actions. The technique is
compatible with conventional methods in that plans are constructed via
an incremental process of introducing actions and posting subgoals. The
key component of the approach is the idea of a secondary precondition.
Whereas primary preconditions define executability conditions of actions,
a secondary precondition defines a context in which an action produces a
desired effect. By introducing and then achieving the appropriate
secondary preconditions as additional subgoals to actions, we ensure
that the actions are carried out in contexts conducive to producing the
effects we desire. The notion of a secondary preconditions will be
defined and analyzed. It will also be shown how secondary preconditions
can be derived in a general and domain-independent fashion for actions
specified in ADL, a STRIPS-like language suitable for describing
context-dependent effects.
------------------------------
Date: Tue, 2 Feb 88 10:46:24 PST
From: JARED%PLU@ames-io.ARPA
Subject: Seminar - AI, NL, and Object-Oriented Databases at HP (NASA)
National Aeronautics and Space Administration
Ames Research Center
SEMINAR ANNOUNCEMENT
SPEAKER: Dr. Steven Rosenberg
Hewlett Packard, HP Labs
TOPIC: AI, Natural Language, and Object-Oriented Databases at HP
ABSTRACT:
Hewlett Packard Labs is the research arm of the Hewlett Packard Corporation.
HP labs conducts research in technologies ranging from AI to super-
conductivity. A brief overview of computer science research at HP Labs
will be presented with a focus on AI, Natural Language, and object-oriented
databases.
BIOGRAPHY:
Dr. Steven Rosenberg is the former department manager, Expert Systems
Department, Hewlett-Packard Laboratories. Prior to joining HP, he worked
at the Lawrence Berkeley Laboratories, and at the MIT AI Lab. At HP
he has led the development of expert systems such as Photolithography
Advisor, an expert system that diagnoses wafer flaws due to photolithography
errors, and recommends corrective action. He has also led the development
of expert system programming languages such as HP-RL, an expert system
language that has been used within HP and at several universities for
constructing expert systems. He is currently involved in developing new
research collaborations between HP and the university community.
DATE: Tuesday, TIME: 1:30 - 3:00 pm BLDG. 244 Room 103
February 9, 1988 --------------
POINT OF CONTACT: Marlene Chin PHONE NUMBER: (415) 694-6525
NET ADDRESS: chin%plu@ames-io.arpa
***************************************************************************
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.
***************************************************************************
------------------------------
Date: Mon, 1 Feb 88 14:13:38 EST
From: jose@tractatus.bellcore.com (Stephen J. Hanson)
Subject: Conference - Connectionist Modeling and Brain Function
(Princeton)
Connectionist Modeling and Brain Function:
The Developing Interface
February 25-26, 1988
Princeton University
Lewis Thomas Auditorium
This symposium explores the interface between connectionist modeling
and neuroscience by bringing together pairs of collaborating speakers
or researchers working on related problems. The speakers will consider
the current state and future prospects of four fields in which convergence
between experimental and computational approaches is developing rapidly.
Thursday Friday
Associative Memory and Learning Sensory Development and Plasticity
9:00 am 9:00 am
Introductory Remarks Preliminaries
Professor G. A. Miller Announcements
9:15 am 9:15 am
Olfactory Process and Associative Role of Neural Activity in the
Memory: Cellular and Modeling Development of the Central Visual
Studies System: Phenomena, Possible Mechanism
and a Model
Professor A. Gelperin Professor Michael P. Stryker
AT&T Bell Laboratories University of California, San Francisco
Princeton University
10:30 am 10:30 am
Simple Neural Models of Towards an Organizing Principle for a
Classical Conditioning Perceptual Network
Dr. G. Tesauro Dr. R. Linsker, M.D., Ph.D.
Center for Complex Systems Research IBM Watson Research Lab
Noon-Lunch Noon-Lunch
1:30 pm 1:30 pm
Brain Rhythms and Network Memories: Biological Constraints on a Dynamic
I. Rhythms Drive Synaptic Change Network: Somatosensory Nervous System
Professor G. Lynch Dr. T. Allard
University of California, Irvine University of California, San Francisco
3:00 pm 3:00 pm
Brain Rhythms and Network Memories: Computer Simulation of Representational
II. Rhythms Encode Memory Plasticity in Somatosensory Cortical
Hierarchies Maps
Professor R. Granger Professor Leif H. Finkel
University of California, Irvine Rockefeller University
The Neuroscience Institute
4:30 pm General Discussion 4:30 pm General Discussion
5:30 pm Reception 5:30 pm Reception
Green Hall, Langfeld Lounge Green Hall, Langfeld Lounge
Organizers Sponsored by
Stephen J. Hanson Bellcore & Department of Psychology
Princeton U. Cognitive Science Laboratory
Carl R. Olson Princeton U. Human Information Processing Group
George A. Miller, Princeton U.
Travel Information
Princeton is located in central New Jersey, approximately 50 miles
southwest of New York City and 45 miles northest of Philadelphia. To
reach Princeton by public transportation, one usually travels through
one of these cities. We recommend the following routes:
By Car
>From NEW YORK - - New Jersey Turnpike to Exit #9, New Brunswick; Route
18 West (approximately 1 mile) to U.S. Route #1 South, Trenton. From
PHILADELPHIA - - Interstate 95 to U.S. Route #1 North. From
Washington - - New Jersey Turnpike to Exit #8, Hightstown; Route 571.
Princeton University is located one mile west of U.S. Route #1. It
can be reached via Washington Road, which crosses U.S. Route #1 at the
Penns Neck Intersection.
By Train
Take Amtrak or New Jersey Transit train to Princeton Junction, from
which you can ride the shuttle train (known locally as the "Dinky")
into Princeton. Please consult the Campus Map below for directions on
walking to Lewis Thomas Hall from the Dinky Station.
For any further information concerning the conference please
contact our conference planner:
Ms. Shari Landes
Psychology Department
Princeton University, 08544
Phone: 609-452-4663
Elec. Mail: shari@mind.princeton.edu
------------------------------
Date: Thu 4 Feb 88 00:29:33-EST
From: Dave.Touretzky@C.CS.CMU.EDU
Subject: Course - Connectionist Summer School
Subject: revised and final call for applications
THE 1988 CONNECTIONIST MODELS SUMMER SCHOOL
ORGANIZER: David Touretzky
ADVISORY COMMITTEE: Geoffrey Hinton, Terrence Sejnowski
SPONSORS: The Sloan Foundation; AAAI; AFOSR; in cooperation with ACM SIGART.
DATES: June 17-26, 1988
PLACE: Carnegie Mellon University, Pittsburgh, Pennsylvania
PROGRAM: The summer school program is designed to introduce young neural
networks researchers to the latest developments in the field. There will be
sessions on learning, theoretical analysis, connectionist symbol processing,
speech recognition, language understanding, brain structure, and neuromorphic
computer architectures. Students will have the opportunity to informally
present their own research and to interact closely with some of the leaders of
the field.
LIST OF FACULTY:
Yaser Abu-Mostafa (Caltech) Yann Le Cun (Toronto)
Dana Ballard (Rochester) James McClelland (Carnegie Mellon)
Andrew Barto (U. Mass.) David Rumelhart (Stanford)
Gail Carpenter (Boston U.) Terrence Sejnowski (Johns Hopkins)
Scott Fahlman (Carnegie Mellon) Mass Sivilotti (Cal Tech)
Geoffrey Hinton (Toronto) Paul Smolensky (UC Boulder)
Michael Jordan (MIT) David Tank (AT&T Bell Labs)
Scott Kirkpatrick (IBM) David Touretzky (Carnegie Mellon)
George Lakoff (Berkeley) Alex Waibel (ATR International)
EXPENSES: Students are responsible for their meals and travel expenses; a small
amount of travel funds may be available. Free dormitory space will be
provided. There is no tuition charge.
WHO SHOULD APPLY: The summer school's goal is to assist young researchers who
have chosen to work in the area of neural computation. Participation is
limited to graduate students (masters or doctoral level) who are actively
involved in some aspect of neural network research. Persons who have already
completed the Ph.D. are not eligible. Applicants who are not full time
students will still be considered, provided that they are enrolled in a
doctoral degree program. A total of 50 students will be accepted.
HOW TO APPLY: By March 1, 1988, send your curriculum vitae and a copy of one
relevant paper, technical report, or research proposal to: Dr. David Touretzky,
Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, 15213.
Applicants will be notified of acceptance by April 15, 1988.
------------------------------
End of AIList Digest
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