LAWS@SRI-AI.ARPA (03/04/85)
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-AI.ARPA>
AIList Digest Monday, 4 Mar 1985 Volume 3 : Issue 28
Today's Topics:
Knowledge Representation - Attribution of Characteristics &
RETE Algorithm & Commonsense and Qualitative Reasoning,
AI Tools - KEE Unification & XLISP,
Seminar Summary - Representational Cognitive Modeling (CSLI),
Seminars - Varieties of Phenomenology (UCB) &
Prolog, Databases, and Natural Language Access (SU) &
Connectionist Inference Architecture (CMU) &
Animating Programs Using Smalltalk (GE)
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Date: 1 Mar 85 07:50:00 EST
From: bogner@ari-hq1
Reply-to: <bogner@ari-hq1>
Subject: ATTRIBUTION OF CHARACTERISTICS
I AM COLLECTING DATA FOR A KNOWLEDGE REPRESENTATION MODEL, ON THE ATTRIBUTION
OF CHARACTERISTICS TO INDIVIDUALS USING A MODIFICATION OF GEORGE KELLY'S
REP GRID. I AM DEVELOPING AN ARGUMENT AGAINST ATTRIBUTION ALONG BIPOLAR
DIMENSIONS (BOUNDED BY ANTONYMS). IS ANYONE ELSE ADDRESSING THAT OR A
SIMILAR QUESTION???
I WOULD GREATLY APPRECIATE LISTINGS OF ANY RELATED CONFERENCES, MEETINGS,
TUTORIALS, . . .
SUE
------------------------------
Date: 1 Mar 1985 9:08:28 EST (Friday)
From: Karl Schwamb <m13820@mitre>
Subject: RETE Algorithm
This is in replay to Don Rose's message to the AIList (V 3, N 27).
The two references below are an excellent place to start learning about
the RETE algorithm:
C. L. Forgy, "Rete: A Fast Algorithm for the Many Pattern/Many Object
Pattern Match Problem," in ARTIFICIAL INTELLIGENCE (V 19, N 1).
C. L. Forgy, On the efficient implementation of production systems,
Ph.D. Thesis, Carnegie-Mellon Univ., 1979.
Hope this helps! ...Karl
------------------------------
Date: 1 Mar 85 08:20 PST
From: Bobrow.pa@XEROX.ARPA
Subject: Commonsense Reasoning
From: arora@buffalo (Kulbir S. Arora)
Subject: Request for bibliography
Is there a bibliography available on Common-sense reasoning systems
(qualitative reasoning, mental models) ?
Kulbir Arora
Volume 24 of the AI Journal was devoted to Qualitative Reasoning about
Physical Systems, and is now avalailable as a book from MIT Press.
danny bobrow
------------------------------
Date: Fri, 1 Mar 85 17:12 EST
From: Paul Fishwick <Fishwick%upenn.csnet@csnet-relay.arpa>
Subject: Qualitative Reasoning
As to the request for a bibiliography for qualitative reasoning, I
suggest reviewing the following 2 references:
1) "Mental Models", edited by Gentner, Dedre and Stevens, Albert,
Lawrence Erlbaum Associates, Hillsdale, New Jersey 1983.
2) Special Issue of the Artificial Intelligence Journal: Volume 24,
numbers 1-3, December 1984.
They contain a number of very good papers in addition to further
references for more specific topics within QR.
-paul
------------------------------
Date: Sun 3 Mar 85 08:49:32-PST
From: Richard Fikes <FIKES@USC-ECL.ARPA>
Subject: Rule Systems Using Unification
Regarding your query about production rule systems and unification --
The rule system in IntelliCorp's KEE system (Release 2.0) uses full
unification to match rules to goals, subgoals, and items retrieved
from the knowledge base. It has both a forward chainer and a backward
chainer.
richard fikes
(FIKES@USC-ECL)
------------------------------
Date: Friday, 1 Mar 1985 06:37:27-PST
From: minow%rex.DEC@decwrl.ARPA
Subject: XLISP
Re: XLISP question in AIList V3.27
There is an article on XLISP in the March 85 Byte magazine. Also,
the recent USENET distribution of XLISP mentioned that the author,
Dave Betz, can be reached as "harvard!betz". I don't know the
USENET path to harvard, nor do I know if betz@harvard.arpa would
work.
Dave's a good guy, please don't bother him with questions if you
haven't read the article (and the code/documentation/examples).
Martin Minow
minow%rex.dec@decwrl.arpa
------------------------------
Date: 1 Mar 1985 1656 PST
From: Larry Carroll <LARRY@JPL-VLSI.ARPA>
Reply-to: LARRY@JPL-VLSI.ARPA
Subject: XLISP
The latest Byte (March '85) has an article by the author of XLISP, David
Betz. It includes a fairly clear explanation of the concepts you're
having trouble with and some examples.
Larry @ jpl-vlsi
------------------------------
Date: Fri, 1 Mar 85 18:28:31 PST
From: Richard K. Jennings <jennings@AEROSPACE.ARPA>
Subject: XLISP 1.4
The current issue of Byte (March 85) has an excellent article
on XLISP by its creator David Betz. In it he mentions version 1.4
which is supposed to be similar to Common Lisp. Anybody know where a
copy can be obtained?
Rich.
------------------------------
Date: Sun, 3 Mar 85 16:00:23 PST
From: Richard K. Jennings <jennings@AEROSPACE.ARPA>
Subject: XLISP
I am in the process of getting the newest version of XLISP to run
on an IBM-PC-AT/DOS 3.0/Computer Innovations ver 2.1/ big-dos2-soft
model. The source is available at HARVARD, which accepts an
anonymous login.
In order to get the thing to recompile (almost 1 hr), some changes
had to be made, described below. Although I have just started to
test it out, any obvious mistakes I may have made I would appreciate
hearing about from an observant reader.
[XLISP ver 1.4 is a public domain version of a COMMON LISP, new
with version 1.4, which was authored and maintained by David Betz]
[The source is 170K, .EXE is 70K, and the manual is 30p]
[Also see March 85 BYTE for an article by Betz on XLISP]
Changes:
1) NIL => 0 from (NODE *) 0
2) deleted references to xlintern()
3) used standard unix "setjmp.h" (bsd 4.1)
4) used a dummy "ctype.h"
The file available on HARVARD is a shell file. Since I am not
running under unix, I had to kludge my own decommutator which I
can send upon request.
Richard K Jennings
AF Sat Cntl Fac
408 744-6427 av: 799-6427 arpa: jennings@aerospace
afscf.xrp@hq-afsc
------------------------------
Date: Thu 21 Feb 85 14:50:16-PST
From: Emma Pease <Emma@SU-CSLI.ARPA>
Subject: Seminar Summary - Representational Cognitive Modeling (CSLI)
[Excerpted from the CSLI Newsletter by Laws@SRI-AI.]
SUMMARY OF F4 MEETING
At the meeting of project F4 on February 11, Bob Moore presented
arguments for the representational approach to designing AI systems
and modelling mental activities in humans. Moore first noted the
relative ease with which a human can acquire individual beliefs
without disturbing very much of the rest of his mental state. This
supports the idea that distinct beliefs ought to be embodied
more-or-less individually, since acquiring a new belief does not seem
to require wholesale reorganization of one's mental state. Moore went
on to argue that the combinatorial structure of what can be believed
suggests a similar combinatorial structure to how it is believed. The
idea is that the combinatorial structure of the sentences used to
characterize belief states does not serve merely to distinguish one
belief state from another; there are regularities in behavior that
depend on that structure. For instance, having a belief of the form
``if not P, then Q'' is associated with behavior appropriate to Q's
being true when evidence of P's being false is presented, but not
necessarily with behavior appropriate to P's being true when evidence
of Q's being false is presented, even though ``if not P, then Q'' and
``if not Q, then P'' are equivalent under most interpretations of the
conditional. The fact that this and many other structural
distinctions in sentences used to classify belief states correspond to
systematic distinctions in behavior presents a prima facie case that
the belief states themselves are similarly structured. But, Moore
argued, under a conception of representation sufficiently abstract to
cover the kinds of ``representation'' actually used in computational
models of mental states, the claim that mental states involve
``syntactic'' representations--a language of thought--probably comes
to no more than this. Moore concluded by noting that none of these
arguments bear on the question of whether the language of thought is
distinct from natural language, but that empirical considerations,
such as the indexicality of natural language and the difficulty of
stating principles of reasoning that apply directly to natural
language, suggest that the two are distinct.
------------------------------
Date: Wed, 27 Feb 85 16:15:29 pst
From: chertok%ucbkim@Berkeley (Paula Chertok)
Subject: Seminar - Varieties of Phenomenology (UCB)
BERKELEY COGNITIVE SCIENCE PROGRAM
Spring 1985
Cognitive Science Seminar -- IDS 237B
TIME: Tuesday, March 5, 11 - 12:30
PLACE: 240 Bechtel Engineering Center
(followed by)
DISCUSSION: 12:30 - 2 in 200 Building T-4
SPEAKER: Hubert Dreyfus, Department of Philosophy, UC
Berkeley
TITLE: ``Varieties of Phenomenology: Husserl, Heidegger
and Merleau-Ponty''
A tutorial review of the three most important accounts of
intentionality in recent continental philosophy, with emphasis on
their relevance to current theories of mental representation.
Edmund Husserl begins the phenomenological concern with inten-
tionality. In his earlier work, The LOGICAL INVESTIGATIONS, he
holds a view similar to Searle's that intentional content type
individuates mental acts. Later, in IDEAS, he changes to a posi-
tion, which he calls ``cognitive science,'' in which mental
representations are held to be hierarchies of strict rules,
involved in all intelligent activity. I take this to be an early
version of the computational view of the mind.
Husserl's account leads to two important counter-views.
Martin Heidegger in BEING AND TIME argues that intentional states
do not play the central role in intelligent behavior Husserl sup-
posed, and that even in those cases where intentional states are
involved their intentional content can not be treated as abstract
structures. Maurice Merleau-Ponty, like Heidegger, argues for a
primitive form of intentionality which does not involve mental
representation, but whereas Heidegger is primarily interested in
an account of action and its social setting, Merleau-Ponty bases
his critique on a phenomenology of perception and bodily skills.
Together, Heidegger's and Merleau-Ponty's work constitutes
the most powerful critique of cognitivism so far offered.
------------------------------
Date: Thu 28 Feb 85 09:51:18-PST
From: Gio Wiederhold <WIEDERHOLD@SU-SCORE.ARPA>
Subject: Seminar - PROLOG, DATABASES, AND NATURAL LANGUAGE ACCESS (SU)
[Forwarded from the Stanford bboard by Laws@SRI-AI.]
CS 300 -- Computer Science Department Colloquium -- Winter 1984-1985.
Tuesday, March 5, 1985
at 4:15 in Terman Auditorium
PROLOG, DATABASES, AND NATURAL LANGUAGE ACCESS
David H.D. WARREN
Quintus Computer Systems, Inc.
PROLOG is a general purpose programming language based on logic. It
can be viewed either as an extension of pure LISP, or as an extension
of a relational database query language. It was first conceived in
1972, by Alain Colmerauer at the University of Marseille. Since then,
it has been used in a wide variety of applications, including natural
language processing, algebraic symbol manipulation, compiler writing,
architectural design, VLSI circuit design, and expert systems. PROLOG
was chosen as the initial kernel language for Japan's Fifth Generation
Computer Systems project, and the project's prototype Prolog machine,
PSI, has recently been unveiled in Tokyo.
In this talk, I will give an overview of the language, and then focus
on one particular application, a domain-independent system for natural
language question answering, called "CHAT". I will compare the way
Chat plans and executes a query with the query optimization strategies
of relational database systems such as SYSTEM-R. Finally I will
discuss the future prospects for PROLOG in the light of Japan's Fifth
Generation project, and describe the high-performance PROLOG systems
for the SUN and VAX available from Quintus.
------------------------------
Date: Friday, 1 March 1985 15:56:29 EST
From: Steven.Shafer@cmu-cs-ius.arpa
Subject: Seminar - Connectionist Inference Architecture (CMU)
AI SEMINAR
Symbols Among the Neurons: Details of a Connectionist Inference Architecture
Dave Touretzky, CMU
Tuesday, March 5, 3:00 pm in WeH 5409
Pattern matching and variable binding are easily implemented in
conventional computer architectures, but not necessarily in all
architectures. In a distributed neural network architecture each
symbol is represented by activity in many units and each unit
contributes to the representation of many symbols. Manipulating
symbols using this type of representation is not as easy as with a
local representation where each unit denotes one symbol, but there
is evidence that the distributed approach is the one chosen by
nature. In this talk I will describe work I am doing with Geoff
Hinton on production system interpreters implemented in neural
networks using distributed representations for both symbols and
rules. The research provides an account of two important symbolic
reasoning operations, pattern matching and variable binding, as
emergent properties of collections of neuron-like elements. The
success of our production system implementations goes some way
towards answering a common criticism of connectionist theories:
that they aren't powerful enough to do symbolic reasoning.
------------------------------
Date: Tue, 26 Feb 85 15:13:02 EST
From: coopercc@GE-CRD
Subject: Seminar - Animating Programs Using Smalltalk (GE)
Computer Science Seminar
General Electric R & D Center
Schenectady, N.Y.
Animating Programs Using Smalltalk
Ralph L. London
Tektronix, Inc.
Friday, March 15
1:30 PM, Bldg. K1, Conf. Rm. 2
(Refreshments at 1:15)
ABSTRACT: We discuss our work in program animation
using the Smalltalk programming environment. We strive
to isolate the graphical viewing structure from the
code of the algorithm being animated. In addition to
"procedure calls" this is achieved through a refinement
of the Smalltalk Model-View-Controller construct and
view dependency mechanism, which allows the algorithm
code to broadcast interesting events and supports the
insertion of probes into active values. Multiple, dif-
ferent views of a single object are easily achieved.
There are connections between interesting events and
invariant assertions. Further efforts were made to
ensure smoothness of motion and transitions between
states. A number of particular animations, the evolu-
tion of an animation, and directions for further
research are included. We plan to show a videotape.
Notice to Non-GE attendees:
It is necessary that we ask you to notify Marion White
(518-385-8370 or WHITEMM@GE-CRD) at least two days in
advance of the seminar.
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End of AIList Digest
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