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AIList Digest Volume 8 Issue 085
AIList Digest Friday, 16 Sep 1988 Volume 8 : Issue 85
Seminars:
Expert Systems for Agriculture Workshop
Parallel Symbolic Computing Using Multilisp
The Representation of Pronouns and Definite Noun Phrases
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Date: Tue, 6 Sep 88 10:43:34 CDT
From: dale@topaz.tamu.edu (A. Dale Whittaker)
Subject: Expert Systems for Agriculture Workshop
A first-of-its-kind workshop on the integration of expert systems with
conventional problem solving techniques for agricultural problems was
held in San Antonio, Texas on August 10 through 12, 1988. This workshop was
supported by the American Association for Artificial Intelligence (AAAI)
and by the Knowledge Systems Area of the American Society of
Agricultural Engineering (ASAE). The meeting was part of the AAAI
workshop series on applied topics and was focused toward agriculture.
Agriculture is an area of enormous potential for appli-
cations of integrated knowledge-based/conventional technolo-
gies. For example, excellent databases are available for
information ranging from historical weather data to indivi-
dual dairy cow records. Complex simulations have been
developed to describe phenomena ranging from plant growth to
economic systems. These investments are a valuable asset as
knowledge sources for knowledge-based decision making.
The primary goals of this meeting were to:
- assess the state-of-the-art of integrated systems for
agriculture.
- determine what factors are necessary to advance the
state-of-the-art.
- expose research needs and opportunities for the future.
- form an interdisciplinary core of researchers for
future communication and collaboration.
A wide variety of research organizations were
represented at the meeting including:
Department of Entomology, Texas A&M University
Department of Entomology, University of Massachusetts
School of Computer Science, Rochester Institute of
Technology
Department of Statistics, North Carolina State Univer-
sity
Agricultural Engineering Department, Texas A&M Univer-
sity
Honeywell-Bull, Knowledge Engineering Services
Texas Agricultural Experiment Station
United States Dept. of Agri., Agricultural Research
Service (Texas, Arizona, Nebraska)
International Maize and Wheat Improvement Center, Cali,
Columbia
Animal Science Department, Oklahoma State University
Department of Agricultural and Applied Economics, Univ.
of Minn.
Department of Agricultural Economics, Univ. of Arkansas
Agricultural Engineering Department, Purdue University
Institute of Food and Agricultural Sciences, Univ. of
Fla.
Topics presented included:
The state of the Art and Future of Symbolic and Numeric
Computation: Hardware Industry Viewpoint
EASY-MACS: A Knowledge-based System Supporting IPM
Decision Making in Apples
Integrating a Knowledge-based Meat Grading System with
a Voice-input Device
Expert System and Conventional Programming Methods for
Small Farm Planning
A Blackboard Approach for Integrating Expert Systems
with Conventional Problem Solving Techniques
The State of the Art and Future of Symbolic and Numeric
Computation: Software Industry Viewpoint
The Use of Expert System Techniques and Database Files
to Produce Customized Decision Aid Software
COTFLEX: An Integrated Expert and Database System for
Decision Support in Texas Cotton Production
Use of an Expert System to Derive Pesticide Groundwater
Contamination Recommendations
An Expert System to Elicit Risk Preferences: The
Futility of Utility Revisited
Developing Integrated Decision Support Systems Using
Prolog
Decision Analysis as a Tool for Integrating Simulation
with Expert Systems When Risk and Uncertainty are
Important
Farm Application of GOSSYM/COMAX
Integrated Expert System for Culling Management of Beef
Cows
****************************************************************************
For more information concerning the workshop, contact:
A. Dale Whittaker
Agricultural Engineering Dept.
Texas A&M University
College Station, TX 77843-2117
dale@topaz.tamu.edu
(409)845-8379
------------------------------
Date: Tue, 06 Sep 88 16:35:08 EDT
From: "Peter Mager" <met9i7n%BUACCA.BITNET@MITVMA.MIT.EDU>
Subject: Parallel Symbolic Computing Using Multilisp
The following seminar may be of interest to AI list subscribers:
ACM GREATER BOSTON CHAPTER SICPLAN
Thursday, September 8, 1988
8 P.M.
Bolt Beranek and Newman, Newman auditorium
70 Fawcett St., Cambridge
Parallel Symbolic Computing Using Multilisp
Robert H. Halstead, Jr.
Laboratory for Computer Science
MIT
Multilisp is an extension of the Lisp dialect Scheme with
additional operators and additional semantics for parallel
execution. The principal parallelism construct in Multilisp is the
"future," which exhibits some features of both eager and lazy
evaluation. Multilisp has been implemented, and runs on the
shared-memory Concert multiprocessor, using as many as 34
processors. The implementation uses interesting techniques for task
scheduling and garbage collection. The task scheduler helps control
excessive resource utilization by means of an unfair scheduling
policy; the garbage collector uses a multiprocessor algorithm
modeled after the incremental garbage collector of Baker.
Current work focuses on making Multilisp a more humane programming
environment, on expanding the power of Multilisp to express task
scheduling policies, and on measuring the properties of Multilisp
programs with the goal of designing a parallel architecture well
tailored for efficient Multilisp execution. The talk will briefly
describe Multilisp, discuss the areas of current activity, and
outline the direction of the Multilisp project with special
attention to the areas of task scheduling and architecture design.
------------------------------
Date: Tue 13 Sep 88 15:58:37-EDT
From: Marc Vilain <MVILAIN@G.BBN.COM>
Subject: The Representation of Pronouns and Definite Noun Phrases
BBN Science Development Program
AI Seminar Series Lecture
THE REPRESENTATION OF PRONOUNS AND DEFINITE NOUN PHRASES IN
LOGICAL FORM
Mary P. Harper
Brown University
Computer Science Dept.
(MPH%cs.brown.edu@RELAY.CS.NET)
BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Thursday September 15
Initially, I will discuss the representation of pronouns in logical
form. Two factors influence the representation of pronouns. The first
factor is computational. This factor imposes certain requirements on
the logical form representation of a pronoun. For example, the initial
representation of a pronoun in logical form should be derivable
before its antecedent is known. The antecedent, when determined,
should be specified in a way consistent with the initial representation of
the pronoun. The second factor is linguistic. This factor requires
that the representation for a pronoun should be capable of expressing
the range of behaviors of a pronoun in English, especially in the domain
of verb phrase ellipsis.
I will review past models of verb phrase ellipsis. These models do
not provide a representation of pronouns for computational purposes, and
accordingly fail to meet our computational requirements. Additionally, I will
show that these models fail to represent pronouns in a way which captures the
full range of behaviors of pronouns.
I will then propose a new representation for pronouns and show how this
representation meets our computational requirements while providing a better
model of pronouns in verb phrase ellipsis.
The representation of definite noun phrases will also be discussed. As in
the case of pronouns, there are two factors which influence this representation
(i.e. modeling definite behavior and obeying our computational guidelines).
I will discuss several examples which argue for representing definites as
functions in logical form before pronoun resolution is carried out. I will
discuss the actual representation I chose, and illustrate its use with an
example.
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End of AIList Digest
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