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AIList Digest Volume 3 Issue 136
AIList Digest Monday, 7 Oct 1985 Volume 3 : Issue 136
Today's Topics:
Seminars - Higher-Order Logic Features in Prolog (UPenn) &
Cognitive Science and Computers (UCB) &
The Programmer's Apprentice: KBEmacs (CMU) &
Belief, Awareness, and Limited Reasoning (SU) &
Planning Under Uncertainty using Simulation (SU) &
Aggregation in Qualitative Simulation (MIT) &
Conflict in Problem Solving (MIT) &
Introspection (SU) &
Compact Lisp Machine (SMU),
Seminar Series - IBM Yorktown Projects (Rutgers)
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Date: Sun, 29 Sep 85 10:44 EDT
From: Dale Miller <Dale%upenn.csnet@CSNET-RELAY.ARPA>
Subject: Seminar - Higher-Order Logic Features in Prolog (UPenn)
[Forwarded from the Prolog Digest by Restivo@SU-SCORE.]
A student of mine is holding a seminar at the University of Pennsylvania
that might be of interest to the Prolog bboard readers.
-Dale Miller
Joint Mathematics / Computer Science
LOGIC COLLOQUIUM
Introducing Higher-Order Logic Features into Prolog
Gopalan Nadathur
Monday 30th September 1985
4:40 p.m., DRL 4E17
This talk reports work being undertaken towards a doctoral dissertation
under the supervision of Prof. Dale Miller. This work is motivated by a
desire to examine whether certain features afforded by higher-order logics
are useful in a computational setting.
In this talk we shall present a language that is similar to that of Horn
Clauses of first-order logic except that first-order terms are now replaced
by typed lambda-calculus terms. We shall discuss a theorem-prover based on
higher-order unification for this logic. We shall also attempt to motivate
the usefulness of this language for specifying and performing computations.
We are interested in extending this language by permitting suitably
restricted occurrences of predicate variables, and we shall conclude our
talk by a brief discussion of the issues involved in doing so.
------------------------------
Date: Wed, 2 Oct 85 12:46:31 PDT
From: admin@ucbcogsci.Berkeley.EDU (Cognitive Science Program)
Subject: Seminar - Cognitive Science and Computers (UCB)
BERKELEY COGNITIVE SCIENCE PROGRAM
Fall 1985
Cognitive Science Seminar -- IDS 237A
TIME: Tuesday, October 8, 11:00 - 12:30
PLACE 240 Bechtel Engineering Center
DISCUSSION: 12:30 - 1:30 in 200 Building T-4
SPEAKER: Terry Winograd, Computer Science, Stanford University
TITLE: "What Can Cognitive Science Tell Us About Computers?"
Much work in cognitive science rests on the assumption that
there is a common form of "information processing" that under-
lies human thought and language and that also corresponds to
the ways we can program digital computers. The theory should
then be valid both for explaining the functioning of the
machines (at whatever level of "intelligence") and for under-
standing how they can be integrated into human situations and
activities.
I will argue that theories like those of current cognitive
science are based on a "rationalistic" tradition, which is
appropriate for describing the mechanics of machine operation,
but is inadequate for understanding human cognitive activity
and misleading as a guide to the design and application of
computer technology. The emphasis will be on looking at
alternatives to this tradition, as a starting point for under-
standing what computers really can do.
------------------------------
Date: 1 Oct 1985 1410-EDT
From: Sylvia Brahm <BRAHM@C.CS.CMU.EDU>
Subject: Seminar - The Programmer's Apprentice: KBEmacs (CMU)
SPEAKER: Richard C. Waters (AIL, MIT)
TOPIC: The Programmer's Apprentice: A Session with KBEmacs
WHEN: Friday, October 18, 1985
WHERE: Wean Hall 4605
TIME: 1:30 P.M.
The Knowledge-Based Editor in Emacs (KBEmacs) is the current demonstra-
tion system implemented as part of the Programmer's Apprentice project.
KBEmacs is capable of acting as a semi-expert assistant to a person who
is writing a program -- taking over some parts of the programming task.
Using KBEmacs, it is possible to construct a program by issuing a series
of high level commands. This series of commands can be as much as an
order of magnitude shorter than the program it describes.
KBEmacs is capable of operating on Ada and Lisp programs of realistic
size and complexity. Although KBEmacs is neither fast enough nor robust
enough to be considered a true prototype, both of these problems could
be overcome if the system were to be reimplemented.
------------------------------
Date: Tue 1 Oct 85 08:40:19-PDT
From: Anne Richardson <RICHARDSON@SU-SCORE.ARPA>
Subject: Seminar - Belief, Awareness, and Limited Reasoning (SU)
DAY October 1, 1985
EVENT Computer Science Colloquium
PLACE Skilling Auditorium
TIME 4:15
TITLE Belief, Awareness, and Limited Reasoning
PERSON Dr. Joe Halpern
FROM IBM Corporation
BELIEF, AWARENESS, AND LIMITED REASONING
Classical possible-worlds models for knowledge and belief suffer from the
problem of logical omniscience: agents know all tautologies and their
knowledge is closed under logical consequence. This unfortunately is not a
very accurate account of how people operate! We review possible-worlds
semantics, and then go on to introduce three approaches towards solving the
problem of logical omniscience. In particular, in our logics, the set of
beliefs of an agent does not necessarily contain all valid formulas. One of
our logics deals explicitly with awareness, where, roughly speaking, it is
necessary to be aware of a concept before one can have beliefs about it,
while another gives a model of local reasoning, where an agent is viewed as a
society of minds, each with its own cluster of beliefs, which may contradict
each other. The talk will be completely self-contained.
------------------------------
Date: Tue 1 Oct 85 14:27:13-PDT
From: Alison Grant <GRANT@SUMEX-AIM.ARPA>
Subject: Seminar - Planning Under Uncertainty using Simulation (SU)
Medical Information Sciences Colloquium
Thursday, October 3, 1985
Stanford University Medical Center
Room M-114
1:15-2:15 P.M.
Speaker: Curt Langlotz, MIS Program
Title:
Planning under uncertainty
using probabilistic and symbolic simulation
Artificial intelligence research has largely concentrated on
solving two kinds of planning problems: (1) problems for which there
is certainty about the consequences of action and for which the
planning goals can be met completely (e.g., robot movement between
rooms in a building), and (2) problems for which explicit guidelines
exist for the construction of plans (e.g., the ONCOCIN, MOLGEN, and
ATTENDING programs). However, many planning problems are
characterized by a lack of explicit plan construction guidelines,
goals that are difficult to satisfy completely, and actions whose
consequences cannot be predicted with certainty. This talk will
describe an architecture for planning in such situations and will
outline the motivations behind its design. One key component of this
new architecture is the ability to predict the consequences of plans.
A simulation architecture is currently under development to make these
predictions. It will also be described, along with the motivations
for rejecting existing simulation techniques (both qualitative and
deterministic) in the domain of cancer therapy planning.
------------------------------
Date: Mon, 30 Sep 1985 16:21 EDT
From: Peter de Jong <DEJONG%MIT-OZ at MIT-MC.ARPA>
Reply-to: Cog-Sci-Request%MIT-OZ
Subject: Seminar - Aggregation in Qualitative Simulation (MIT)
[Forwarded from the MIT bboard by SASW@MIT-MC.]
Thursday 3, October 4:00pm Room: NE43- 8th floor Playroom
The Artificial Intelligence Lab
Revolving Seminar Series
"The Use of Aggregation in Qualitative Simulation"
Daniel S. Weld
MIT AI Lab.
I introduce a technique called aggregation which has several
applications to the problem of qualitative simulation and envisioning:
- It can simplify reasoning by dynamically creating more abstract
process descriptions of the types of change occurring in a system.
- It can enable the application of powerful continuous analytic
techniques such as limit analysis to systems whose descriptions
include discrete processes.
- It can direct the reformulation of quantities to more abstract
representations.
Aggregation works by searching the simulation history structure to find
cycles of repeating processes. Once cycles have been detected, a more
abstract continuous process, equivalent to the net effect of the cycle,
is created. Analysis now proceeds on the continuous process.
Aggregation correctly handles cycles that contain other cycles.
A program called PEPTIDE has been written to test these ideas in the
domain of molecular genetics. Paper tests have also been done in the
domains of digital electronics and xerography.
------------------------------
Date: Mon 30 Sep 85 18:18:03-EDT
From: Michael Eisenberg <DUCK%MIT-OZ at MIT-MC.ARPA>
Subject: Seminar - Conflict in Problem Solving (MIT)
[Forwarded from the MIT bboard by Laws@SRI-AI.]
Andre Boder is scheduled to give a talk at the next ideas seminar,
TOMORROW, Tuesday Oct. 1, at 4:30. The talk is scheduled to
be held at the 3rd floor conference room in NE43.
Title: What Is a Conflict in Problem Solving?
I will address the question of why people have difficulty in
problem-solving, arguing that in most cases, a conflict between
incompatible ideas may be evoked. The conjecture is based on the
analysis of familiar-schemes brought to bear in the problem.
I will show that the relation between these schemes may generate
incompatible representations of the same situation. Conflicts
result from difficulty in reducing these incompatibilities.
------------------------------
Date: Thu 3 Oct 85 07:50:26-PDT
From: Ana Haunga <HAUNGA@SUMEX-AIM.ARPA>
Subject: Seminar - Introspection (SU)
SIGLUNCH, Friday, October 4, Chemistry Gazebo, 12:05-1:00.
Introspection
Michael R. Genesereth
Logic Group
Knowledge Systems Laboratory
Stanford University
Abstract: Introspection is a significant part of human mental
activity. We introspect whenever we think about how to solve problem,
whenever we decide what information we need to solve a problem,
whenever we decide that a problem is unsolvable.
By its nature, the process of introspection involves both descriptive
and prescriptive metaknowledge. Over the past years, logicians and AI
researchers have devoted considerable attention to autoepistemic
sentences (involving terms like KNOW). By comparison, little attention
has been paid to prescriptive metaknowledge (involving terms like OUGHT).
This talk introduces a semantics for such knowledge in the form of
constraints on the process of problem solving. It demonstrates the
computational advantages of introspection, and analyzes the
computational fidelity and cost of various introspective
architectures. Finally, it discusses the potential for practical
application in logic programming and building expert systems.
------------------------------
Date: 3 Oct 1985 09:08-CST
From: leff%smu.csnet@CSNET-RELAY.ARPA
Subject: Seminar - Compact Lisp Machine (SMU)
Speaker: Lawerence E. Gene Matthews
Associate Director of the Computer Science Laboratory
Texas Instruments, Dallas
Date: Wednesday, October 16, 1985
Time: 11:30 AM Luncheon
12:15 Program
Place: Richardson Hilton, SW corner of N. Central Expressway & Campbell
The Compact LISP Machine (CLM) development program is the first of
several DARPA programs intended to provide embedded symbolic computing
capbilities for government applications. As one of many contacts
funded under the Strategic Computing Program the CLM will provide
a ruggedized symbolic computer capability for insertion of AI and
robotics technology in awide range of applications.
A description of the four-module CLM system architecture is presented.
Starting with the CLM development goals, a brief system overview and
discussion of advanced software development and maintenance tools are
covered. System and module packaging are described including options
available beyond the scope of the current contract. Each of the four
modules under development are described starting with the CPU module,
which contains the 40 Mhz VLSI CPU chip, and its companion map/cache
module. The module developed for providing physical memory is
described followed by a discussion of the Multibus I/O module which
supports communication between the high performance system bus and
Multibus I. The VLSI LISP processor chip is next described with a
simplified block diagram and packaging information. Finally, some
information on preliminary predicted performance is covered.
Luncheon reservations 995-4440 Monday October 14 $7.00
------------------------------
Date: Wed, 11 Sep 85 13:43:21 EDT
From: Chidanand Apte <Apte.Yktvmv%ibm-sj.csnet@csnet-relay.arpa>
Subject: Seminar Series - IBM Yorktown Projects (Rutgers)
[Forwarded from the Rutgers BBoard by Laws@SRI-AI.]
IBM talks at Rutgers-IBM AI exchange seminar, 10th Oct., Hill Center.
Members of IBM Research from the T.J. Watson Research Center will be
presenting six talks at the 3rd annual Rutgers-IBM AI exchange seminar,
on 10th October 1985, at the Rutgers Computer Science dept. Preliminary
titles and abstracts:
"A representation for complex physical domains"
Sanjaya Addanki
We are exploring a system, called PROMPT, that will be capable of
reasoning from first principles and high level knowledge in complex,
physical domains. Such problem-solving calls for a representation that
will support the different analyses techniques required (e.g.
differential, asymptotic, perturbation etc.). Efficiency considerations
require that the representation also support heuristic control of
reasoning techniques. This talk lays the ground work for our effort by
briefly describing the ontology and the representation scheme of PROMPT.
Our ontology allows reasoning about multiple pasts and different
happenings in the same space-time. The ontology provides important
distinctions between materials, objects, bulk and distributed
abstractions among physical entities. We organize world knowledge into
"prototypes" that are used to focus the reasoning process.
Problem-solving involves reasoning with and modifying prototypes.
"YES/FAME/IDV: An initial approach to a planning consultant for financial
marketing problems"
Chidanand Apte/ Jim Griesmer/ John Kastner/ Yoshio Tozawa
The YES/FAME (Yorktown Expert Systems for Financial and Marketing
Expertise) project is investigating interactive consultants to aid in the
financial marketing of computing technology. Significant expertise
seems to be required in the preparation of a recommendation to a customer
of a technical solution that meets his computing requirements over a
period of time, coupled with a plan for acquiring this technology under
financial terms and conditions that best suit the customer's needs and
concerns. Expertise is also required in generating a convincing financial
argument that will enable the "selling" of this plan. We present in this
talk an overview of an initial demonstration version (YES/FAME/IDV) of a
knowledge based system that illustrates these capabilities for a small
subset of the overall problem.
"Logical extensions of logic programming based on intuitionistic logic"
Seif Haridi
Logic Programming is widely known as programming using Horn clauses. We
extend this paradigm to handle more general relations than Horn clauses.
Based on principles from first order intuitionistic (constructive) logic
we show a much more expressive language with a complete execution
mechanism that is able to handle general first order queries, iterative
and recursive statements, and positive and negative queries with equal
strength. The language has Horn clauses as a subset, and its interpreter
behaves as efficient as a Horn clause (PROLOG) interpreter on that
subset.
"PLNLP: The programming language for natural language processing"
George Heidorn
This talk describes research being done at Yorktown to provide advanced
tools for building knowledge-based systems that involve a large amount
of natural language processing. PLNLP is a programming language based on
the augmented phrase structure grammar formalism that is particularly
well-suited for specifying the processing of natural language text. A
large, broad-coverage English grammar has been written in PLNLP, and
implementations in LISP/VM and PL.8 are currently being used in
applications doing text-critiquing, machine translation, and speech
synthesis. One of these systems, CRITIQUE, will be used as a concrete
illustration of the power of the language.
"YSCOPE: A shell with domain knowledge for solving computer performance
problems"
Joseph Hellerstein
Solving computer-performance problems requires two types of knowledge:
knowledge of the computer system and insights from queueing theory. We
describe the Yorktown Shell for Computer-Performance Experts (YSCOPE)
which is a special-purpose shell that incorporates a knowledge of
queueing theory to facilitate building computer-performance expert
systems.
"Interactive classification in knowledge representations"
Eric Mays
A classifier for a structured representation language allows
semi-automatic maintenance of a knowledge base. However, problems, such
as detecting and recovering from inconsistencies, arise when editing a
KB which has been updated by classifier operations. This talk will
address preliminary investigations along these lines.
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End of AIList Digest
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