WINSLETT@SU-SCORE.ARPA (Marianne Winslett) (03/08/86)
Updating Databases With Incomplete Information
--or--
Belief Revision is Harder Than You Thought
Marianne Winslett
PhD Oral
Area X Seminar
Margaret Jacks 352
Friday, March 14, 3:15 PM
Suppose one wishes to construct, use, and maintain a database of
knowledge about the real world, even though the facts about that world
are only partially known. In the database domain, this situation
arises when database users must coax information into and out of
databases in the face of missing values and uncertainty. In the AI
domain, this problem arises when an agent has a base set of beliefs
that reflect partial knowledge about the world, and then tries to
incorporate new, possibly contradictory knowledge into the old set of
beliefs. In the logic domain, one might choose to represent such a
database as a logical theory, and view the models of the theory as
possible states of the real world.
How can new information (i.e., updates) be incorporated into the
database? For example, given the new information that "b or c is
true," how can we get rid of all outdated information about b and c,
add the new information, and yet in the process not disturb any other
information in the database? The burden may be placed on the user or
other omniscient authority to determine exactly which changes in the
theory will bring about the desired set of models. But what's really
needed is a way to specify an update intensionally, by stating some
well-formed formula that the state of the world is now known to
satisfy and letting the database management system automatically
figure out how to accomplish that update.
This talk will explore a technique for updating databases containing
incomplete information. Our approach embeds the incomplete database
and the updates in the language of first-order logic, which we believe
has strong advantages over relational tables and traditional data
manipulation languages when information is incomplete. We present
semantics and algorithms for our update operators, and describe an
implementation of the algorithms. This talk should be accessible to
all who are comfortable with first-order logic and have a passing
acquaintance with the notion of database updates.
-------tim@LINC.CIS.UPENN.EDU (Tim Finin) (03/06/87)
COLLOQUIUM
Computer and Information Science
University of Pennsylvania
UPDATING DATABASES WITH INCOMPLETE INFORMATION
Marianne Winslett
Stanford University Computer Science Department
Suppose one wishes to construct, use, and maintain a database of facts
about the real world, even though the state of that world is only
partially known. In the artificial intelligence domain, this problem
arises when an agent has a base set of beliefs that reflect partial
knowledge about the world, and then tries to incorporate new, possibly
contradictory knowledge into this set of beliefs. In the database
domain, one facet of this situation is the well-known null
values problem. We choose to represent such a database as a logical
theory, and view the models of the theory as representing possible
states of the world that are consistent with all known information.
How can new information be incorporated into the database? For
example, given the new information that ``b or c is true,'' how can one
get rid of all outdated information about b and c, add the new
information, and yet in the process not disturb any other information
in the database? In current-day database management systems, the
difficult and tedious burden of determining exactly what to add and
remove from the database is placed on the user. The goal of our
research was to relieve users of that burden, by equipping the
database management system with update algorithms that can
automatically determine what to add and remove from the database.
Under our approach, new information about the state of the world is
input to the database management system as a well-formed formula that
the state of the world is now known to satisfy. We have constructed
database update algorithms to interpret this update formula and
incorporate the new information represented by the formula into the
database without further assistance from the user. In this talk we
will show how to embed the incomplete database and the incoming
information in the language of mathematical logic, explain the
semantics of our update operators, and discuss the algorithms that
implement these operators.
March 9, 1987
Room 216 Moore
3:00 to 4:30
Refreshments Available
2:30 to 3:00