Copy Link
Add to Bookmark
Report

AIList Digest Volume 4 Issue 036

eZine's profile picture
Published in 
AIList Digest
 · 1 year ago

AIList Digest           Wednesday, 26 Feb 1986     Volume 4 : Issue 36 

Today's Topics:
Seminars - Solution to the Self-Referential Paradoxes (CSLI) &
Approximate Deduction in Single Evidential Bodies (SRI) &
Refutation Method for Horn Clauses with Equality (UPenn) &
Persistent Memory (SU),
Conferences - Suggestions for AAAI-86 &
Theoretical Issues in NL Processing

----------------------------------------------------------------------

Date: Mon 24 Feb 86 09:04:40-PST
From: Emma Pease <Emma@SU-CSLI.ARPA>
Subject: Seminar - Solution to the Self-Referential Paradoxes (CSLI)


CSLI COLLOQUIUM

LOGIC OF POINTERS AND EVALUATIONS:
THE SOLUTION TO THE SELF-REFERENTIAL PARADOXES
Haim Gaifman
Mathematics Department The Hebrew University Jerusalem Israel
Visiting at SRI
February 27, 1986
Ventura Hall

Imagine the following exchange:

Max: What I am saying at this very moment is nonsense.
Moritz: Yes, what you have just said is nonsense.

Evidently Max spoke nonsense and Moritz spoke to the point. Yet Max
and Moritz appear to have asserted the same thing, namely: that Max
spoke nonsense. Or consider the following two lines:

line 1: The sentence written on line 1 is not true.
line 2: The sentence written on line 1 is not true.

Our natural intuition is that the self-referring sentence on line 1 is
not true (whatever sense could be made of it). Therefore the sentence
on line 2, which asserts this very fact, should be true. But what is
written on line 2 is exactly the same as what is written on line 1.

I shall argue that the unavoidable conclusion is that truth values
should be assigned here to sentence-tokens and that any system in
which truth is only type-dependent (e.g., Kripke's system and its
variants) is inadequate for treating the self-referntial situation.

Since the truth value of a token depends on the tokens to which it
points, whose values depend in their turn on the tokens to which they
point,and so on, the whole network of pointings (which might include
complicated loops) must be taken into account.

I shall present a simple formal way of representing such networks and
an algorithm for evaluating the truth values. On the input 'the
sentence on line 1' it returns GAP but on the input 'the sentence on
line 2' it returns TRUE. And it yields similarly intuitive results in
more complicated situations. For an overall treatment of
self-reference the tokens have to be replaced by the more general
pointers. A pointer is any obgect used to point to a sentence-type (a
token is a special case of pointer it points to the sentence of which
it is a token). Calling a pointer is like a procedural call in a
program, eventually a truth valye (TRUE, FALSE or GAP) is returned -
which is the output of the algorithm.

I shall discuss some more recent work (since my last SRI talk) -
variants of the system and its possible extensions to mathematical
powerful languages. Attempts to make such comprehensive systems throw
new light on the problem of constructing "universal languages".

------------------------------

Date: Mon 24 Feb 86 15:00:13-PST
From: RUSPINI@SRI-AI.ARPA
Subject: Seminar - Approximate Deduction in Single Evidential Bodies (SRI)

AURA (Automated Uncertainty Reasoning Assembly) is about to resume its
AURAcles after some months of suspended animation. The next talk
(abstract below) is scheduled for next Friday, February 28, 10AM at
EK242. We plan to meet as regularly as possible each Friday thereafter
at the same time.



APPROXIMATE DEDUCTION IN
SINGLE EVIDENTIAL BODIES

Enrique H. Ruspini
Artificial Intelligence Center
SRI International

The main objective of this talk is the review of ongoing research on
the interpretation and manipulation of conditional evidence within
single evidential bodies. In the context of a single body of evidence,
conditional evidence is expressed as constraints on the possible
values of propositional truth under the assumption that a specific
proposition within the frame of discernment is known to be true. In
this context deductive inference consists of the combination of the
information about the probable truth of ground propositions (facts)
and conditional evidence (rules) to arrive at new (a posteriori)
estimates of propositional support. This process is both conceptually
and procedurally different from those undertaken when several bodies
of evidence are combined (e.g. using the Dempster Combination Rule).

The role of conditional evidence constraints (henceforth called
approximate or uncertain rules) is examined from the viewpoint of both
the theory of interval probabilities and the Dempster-Shafer Calculus
of Evidence. These approaches to the representation and analysis of
uncertain information will be briefly described together with their
theoretical underpinnings. Several possible interpretations of
approximate rules will be discussed and compared. Possible approaches
for the automation of approximate deduction (under each
interpretation) will also be presented.

Time permitting, the role of these results in the generalization of
Reynold's approach to the generation of support and elementary mass
measures will also be discussed.

------------------------------

Date: Mon, 24 Feb 86 17:25 EST
From: Tim Finin <Tim%upenn.csnet@CSNET-RELAY.ARPA>
Subject: Seminar - Refutation Method for Horn Clauses with Equality (UPenn)

Forwarded From: Dale Miller <Dale@UPenn> on Mon 24 Feb 1986 at 17:08


UPenn Math-CS Logic Seminar
A Refutation Method for Horn Clauses with Equality using E-unification
Jean H. Gallier (with Stan Raatz)

Tuesday, 25 February 1986, 4:30 - 6:00, 4E17 DRL

A refutation method for equational Horn clauses, Horn clauses with or
without equational atoms, is investigated. This method combines standard
SLD-resolution and unification modulo equations. In the case of ground Horn
clauses, unsatisfiability of a set of Horn clauses with equality is
decidable in time O(nlog(n)). In the general case however, even though the
refutation method itself is complete, unification modulo equations is
undecidable. In fact, unification modulo equations is NP-complete even in
the case of ground equations. Considering this point, we explore subcases
of equational Horn clauses for which unification modulo equations is
tractable, and consider the implications for logic programming. Finally, we
compare this new method with other existing methods.

** Next week: G. Rosolini from CMU will speak on "Categories for Partial
Computations".

------------------------------

Date: Mon, 24 Feb 86 23:02:40 pst
From: David Cheriton <cheriton@su-pescadero.arpa>
Subject: Seminar - Persistent Memory (SU)

PERSISTENT OBJECT SYSTEM FOR SYMBOLIC COMPUTERS
Satishe Thatte
Texas Instruments
Thurs. Feb 27th at 4:15 pm.
MJH 352
(Part of Distributed Systems Group Project meeting)

The advent of automatically managed, garbage-collected virtual memory
was crucial to the development of today's symbolic processing. No
analogous capability has yet been developed in the domain of
"persistent" objects managed by a file system or database. As a
consequence, the programmer is forced to flatten rich structures of
objects resident in virtual memory before the objects can be stored in a
file system or conventional database. This task puts a great burden on
the programmer and adversely affects system performance.

A persistent object system that extends the automatic storage management
concepts of a symbolic computer to the domain of persistent objects will
be presented. The system supports long-term, reliable retention of
richly structured objects in virtual memory itself, without resorting to
a file system. Therefore, the system requires a crash recovery scheme
at the level of virtual memory.

The persistent object system is based on a uniform memory abstraction,
which eliminates the distinction between transient objects (data
structures) and persistent objects (files and databases), and therefore,
allows the same set of powerful and flexible operations with equal
efficiency on both transient and persistent objects from a programming
language such as Lisp or Prolog, without requiring a special-purpose database
language. It is expected that the exploitation of such a capability
will lead to significant breakthroughs in knowledge/data base
management.

------------------------------

Date: 25 Feb 86 1016 PST
From: Bob Filman <REF@SU-AI.ARPA>
Subject: Conference - Suggestions for AAAI-86

The deadline for workshop and panel proposals for AAAI-86 is
fast approaching. (Officially, March 1, but we'll give a
few days grace to good ideas.)

Requests for ENGINEERING panels and workshops should be sent to:

Tom Kehler
Program Co-Chairman for AAAI-86
Intellicorp
1975 EL Camino Real West
Mountain View, California 94040
Kehler@USC-ECL.ARPA

Requests for SCIENTIFIC panels and workshops should be sent to:

Stan Rosenschein
Program Co-Chairman for AAAI-86
SRI International
333 Ravenswood Avenue
Menlo Park, California 94025
Stan@SRI-AI.ARPA

------------------------------

Date: Mon, 24 Feb 86 15:58:56 mst
From: "Yorick Wilks <yorick@nmsu>" <yorick@CSNET-RELAY.ARPA>
Subject: Conference - Theoretical Issues in NL Processing

TINLAP3

Third workshop on
Theoretical Issues in Natural Language Processing.
Las Cruces, New Mexico
January 7-9, 1987.

The workshop, supported by the Association for Computational
Linguistics, will follow the format of its predecessors at
MIT (1975), Champaign-Urbana (1978) and Nova Scotia (1985):
panels of distinguished figures in computational linguistics,
AI, and related disciplines will discuss the major topics at issue.
Preliminary registration information: Yorick Wilks, Box3CRL, NMSU, Las
Cruces, NM 88001, or CSNET:az@nmsu.

------------------------------

End of AIList Digest
********************

← previous
next →
loading
sending ...
New to Neperos ? Sign Up for free
download Neperos App from Google Play
install Neperos as PWA

Let's discover also

Recent Articles

Recent Comments

Neperos cookies
This website uses cookies to store your preferences and improve the service. Cookies authorization will allow me and / or my partners to process personal data such as browsing behaviour.

By pressing OK you agree to the Terms of Service and acknowledge the Privacy Policy

By pressing REJECT you will be able to continue to use Neperos (like read articles or write comments) but some important cookies will not be set. This may affect certain features and functions of the platform.
OK
REJECT