AIList-REQUEST@SRI-AI.ARPA (AIList Moderator Kenneth Laws) (10/28/85)
AIList Digest Monday, 28 Oct 1985 Volume 3 : Issue 157
Today's Topics:
Reports - Davis Working Papers in Linguistics,
Seminars - Iterative Knowledge Aggregation (UPenn) &
Limits of Expert Systems (Ames) &
Layered Control System for a Robot (MIT) &
Machine Learning and Knowledge Representation (MIT) &
Possible Histories (SRI)
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Date: Wed, 23 Oct 85 22:20:47 pdt
From: ucdavis!harpo!lakhota@UCB-VAX.Berkeley.EDU
Subject: Davis Working Papers in Linguistics
From: Robert Van Valin, UC Davis
ucdavis!harpo!lakhota@Berkeley
We have started publishing a working paper series at Davis,
and I think there are many linguists on the net who would be
interested in it. Could you run the following blurb for the
first issue in the series? Thanks.
DAVIS WORKING PAPERS IN LINGUISTICS
No. 1, 1985
Contents:
`A lexical theory of auxiliary selection in Italian'
Giulia Centineo, UC Berkeley
`Clause linkage and zero anaphora in Mandarin Chinese'
Liang Tao, UC Davis & Hunan Teacher's College
`Aspects of the interaction of syntax and pragmatics: Discourse
coreference mechanisms and the typology of grammatical systems'
Robert D. Van Valin, Jr., UC Davis
`Notes on Tepehua (Totonacan; Mexico) verbal semantics'
James K. Watters, UC Berkeley & SIL
Approx. 150 pages
[This announcement of the report series is fine, but I have
suppressed price and ordering information to comply with
Arpanet regulations against commercial use. Contact
"ucdavis!harpo!lakhota"@Berkeley for details. -- KIL]
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Date: Thu, 24 Oct 85 00:43 EDT
From: Tim Finin <Tim%upenn.csnet@CSNET-RELAY.ARPA>
Subject: Seminar - Iterative Knowledge Aggregation (UPenn)
12:00 Monday Oct. 28th
303 Towne Building, University of Pennsylvania
A Survey of Iterative Knowledge Aggregation Methods
Robert Hummel
Courant Institute, NYU
Iterative knowledge aggregation methods are used to choose one of a
finite set of labels about each of a set of objects. Relaxation
labeling processes are one example; there are now numerous other
techniques for combining information which is sometimes supportive of
a hypothesis and sometimes mutually contradictory. In this talk, I
compare and contrast these methods, including stochastic relaxation
algorithms, constrained power methods, and the Dempster/Shafer theory
of evidence formulation. For each methods, we review the form of the
state space, the type of evidence which can be represented, and the
updating and convergence properties of the method.
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Date: Thu, 24 Oct 85 21:37:39 pdt
From: eugene@AMES-NAS.ARPA (Eugene Miya)
Subject: Seminar - Limits of Expert Systems (Ames)
Terry Winograd, 11/5, 1030am
National Aeronautics and Space Administration
Ames Research Center
Joint Ames AI Forum/RCR Branch Seminar
SPEAKER: Terry Winograd
Computer Science Dept.
Stanford University
TOPIC: Expert systems: How far can they go?
ABSTRACT: We are in the midst of a great wave of enthusiasm about the
potential for expert systems in every area of human life and work. There is
no agreement, however, as to just how much they can achieve, and where they
will run into fundamental limits. This talk will address some basic
questions as to what expert systems can really be expected to do. I will
describe the "blindness" that is inevitable in the process of articulating
the "systematic domains" that are needed for computer manipulation, and
argue that it leads to important limitations on what we can expect AI
techniques to accomplish.
DATE: 5 Nov. 1985 TIME: 1030am BLDG: 245 ROOM: Space Sci Aud.
Tuesday
POINT OF CONTACT: E. Miya PHONE NUMBER: (415)-694-6453
eugene@ames-nas.ARPA
VISITORS ARE WELCOME: Register and obtain vehicle pass at Ames Visitor
Reception Building (N-253) or the Security Station near Gate 18. See map
below. 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. If you are a foreign
national E-mailing a request, please include your nationality, and
Visa Type and number.
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Date: Sat, 26 Oct 85 16:58:36 EDT
From: "Steven A. Swernofsky" <SASW@MIT-MC.ARPA>
Subject: Seminar - Layered Control System for a Robot (MIT)
Thursday 31, October 4: 00pm Room: NE43- 8th floor Playroom
The Artificial Intelligence Lab
Revolving Seminar Series
"A Layered Robust Control System for a Mobile Robot"
Rod Brooks
MIT AI Lab
The AI Lab Mobile Robot project has built one robot and we are
constructing a second. They are intended to autonomously wander around
office areas of the lab at the same time as people are occupying those
areas. The robots will eventually build maps of their surrondings and
the second one will interact with the environment with an onboard
manipulator. We describe a new architecture for controlling these
mobile robots. Layers of control system are built to let the robot
operate at increasing levels of competence. Layers are made up of
asynchronous modules which communicate over low bandwidth channels.
Each module is an instance of a fairly simple computational machine.
Higher level layers can subsume the roles of lower levels by
suppressing their outputs. However, lower levels continue to function
as higher levels are added. The result is a robust and flexible robot
control system. The talk will end with speculations on evolution and
brains, and modelling them with the Unconnection Machine.
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Date: Sat, 26 Oct 85 17:00:31 EDT
From: "Steven A. Swernofsky" <SASW@MIT-MC.ARPA>
Subject: Seminar - Machine Learning and Knowledge Representation (MIT)
Wednesday 30, October 4: 00pm Room: 405 Robinson Hall
Northeastern University
360 Huntington Ave.
Boston MA
Northeastern University
College of Computer Science Colloquium
Brittleness, Tunnel Vision, Machine Learning and
Knowledge Representation
Prof. Steve Gallant
Northeastern University
A system is brittle if it fails when presented with slight deviations from
expected input. This is a major problem with knowledge representation schemes
and particularly with expert systems which use them.
This talk defines the notion of Tunnel Vision and shows it to be a major
cause of brittleness. As a consequence it will be claimed that commonly
used schemes for machine learning and knowledge representation are pre-
disposed toward brittle behavior. These include decision trees, frames,
and disjunctive normal form expressions.
Some systems which are free from tunnel vision will be described.
INFO: Carole D Hafner <HAFNER%northeastern.csnet@CSNET-RELAY.ARPA>
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Date: Sun 27 Oct 85 18:48:47-PST
From: LANSKY@SRI-AI.ARPA
Subject: Seminar - Possible Histories (SRI)
POSSIBLE HISTORIES
Pat Hayes
Schlumberger Palo Alto Research, AI Lab
11:00 AM, MONDAY, October 28
SRI International, Building E, Room EJ228 (new conference room)
A history is a connected piece of space/time with 'natural' boundaries.
Using these as a basic ontology for talking about events, processes, etc.
has some advantages over some other frameworks, and doesn't have some of
the disadvantages which are sometimes attributed to it.
However, it does have one major problem, which is the difficulty of talking
about alternative possible futures, to allow planning to be done.
In this talk I discuss a new way of using histories which looks like
it can overcome this problem.
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End of AIList Digest
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