Uncertainty in Knowledge Bases

The management and processing of uncertain information has
shown itself to   be a crucial issue in the development of
intelligent systems, beginning withits appearance in the
such systems as Mycin and Prospector. The papers in   this
volume reflect the current range of interests or researchers
in thefield. Currently, the major approaches to uncertainty
include fuzzy set      theory, probabilistic methods,
mathematical theory of evidence, non-standardlogics such as
default reasoning, and possibility theory.
The initial   part of the volume is devoted to papers dealing
with the foundations of      these approaches, where recent
attempts have been made to develop systems   combining
multiple approaches. A significant part of the book looks            at
the management of uncertainty in a number of the
paradigmatic domainsof intelligent systems such as expert
systems, decision making, databases,   image processing, and
reasoning networks.
The papers are extended         versions of presentations at the
third international conference on               information processing and
management of uncertainty in knowledge-based      systems. The
proceedings of the two preceding IPMU conferences appear         as
LNCS 286 and LNCS 313.